amusi / cvpr2024-papers-with-code

CVPR 2024 论文和开源项目合集

CVPR 2024 论文和开源项目合集(Papers with Code)

CVPR 2024 decisions are now available on OpenReview！

注1：欢迎各位大佬提交issue，分享CVPR 2024论文和开源项目！

注2：关于往年CV顶会论文以及其他优质CV论文和大盘点，详见： https://github.com/amusi/daily-paper-computer-vision

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【CVPR 2024 论文开源目录】

• 3DGS(Gaussian Splatting)
• Avatars
• Backbone
• CLIP
• MAE
• Embodied AI
• GAN
• GNN
• 多模态大语言模型(MLLM)
• 大语言模型(LLM)
• NAS
• OCR
• NeRF
• DETR
• Prompt
• 扩散模型(Diffusion Models)
• ReID(重识别)
• 长尾分布(Long-Tail)
• Vision Transformer
• 视觉和语言(Vision-Language)
• 自监督学习(Self-supervised Learning)
• 数据增强(Data Augmentation)
• 目标检测(Object Detection)
• 异常检测(Anomaly Detection)
• 目标跟踪(Visual Tracking)
• 语义分割(Semantic Segmentation)
• 实例分割(Instance Segmentation)
• 全景分割(Panoptic Segmentation)
• 医学图像(Medical Image)
• 医学图像分割(Medical Image Segmentation)
• 视频目标分割(Video Object Segmentation)
• 视频实例分割(Video Instance Segmentation)
• 参考图像分割(Referring Image Segmentation)
• 图像抠图(Image Matting)
• 图像编辑(Image Editing)
• Low-level Vision
• 超分辨率(Super-Resolution)
• 去噪(Denoising)
• 去模糊(Deblur)
• 自动驾驶(Autonomous Driving)
• 3D点云(3D Point Cloud)
• 3D目标检测(3D Object Detection)
• 3D语义分割(3D Semantic Segmentation)
• 3D目标跟踪(3D Object Tracking)
• 3D语义场景补全(3D Semantic Scene Completion)
• 3D配准(3D Registration)
• 3D人体姿态估计(3D Human Pose Estimation)
• 3D人体Mesh估计(3D Human Mesh Estimation)
• 医学图像(Medical Image)
• 图像生成(Image Generation)
• 视频生成(Video Generation)
• 3D生成(3D Generation)
• 视频理解(Video Understanding)
• 行为检测(Action Detection)
• 文本检测(Text Detection)
• 知识蒸馏(Knowledge Distillation)
• 模型剪枝(Model Pruning)
• 图像压缩(Image Compression)
• 三维重建(3D Reconstruction)
• 深度估计(Depth Estimation)
• 轨迹预测(Trajectory Prediction)
• 车道线检测(Lane Detection)
• 图像描述(Image Captioning)
• 视觉问答(Visual Question Answering)
• 手语识别(Sign Language Recognition)
• 视频预测(Video Prediction)
• 新视点合成(Novel View Synthesis)
• Zero-Shot Learning(零样本学习)
• 立体匹配(Stereo Matching)
• 特征匹配(Feature Matching)
• 场景图生成(Scene Graph Generation)
• 隐式神经表示(Implicit Neural Representations)
• 图像质量评价(Image Quality Assessment)
• 视频质量评价(Video Quality Assessment)
• 数据集(Datasets)
• 新任务(New Tasks)
• 其他(Others)

3DGS(Gaussian Splatting)

Scaffold-GS: Structured 3D Gaussians for View-Adaptive Rendering

• Homepage: https://city-super.github.io/scaffold-gs/
• Paper: https://arxiv.org/abs/2312.00109
• Code: https://github.com/city-super/Scaffold-GS

GPS-Gaussian: Generalizable Pixel-wise 3D Gaussian Splatting for Real-time Human Novel View Synthesis

• Homepage: https://shunyuanzheng.github.io/GPS-Gaussian
• Paper: https://arxiv.org/abs/2312.02155
• Code: https://github.com/ShunyuanZheng/GPS-Gaussian

GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussians

• Paper: https://arxiv.org/abs/2312.02134
• Code: https://github.com/huliangxiao/GaussianAvatar

GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splatting

• Paper: https://arxiv.org/abs/2311.14521
• Code: https://github.com/buaacyw/GaussianEditor

Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction

• Homepage: https://ingra14m.github.io/Deformable-Gaussians/
• Paper: https://arxiv.org/abs/2309.13101
• Code: https://github.com/ingra14m/Deformable-3D-Gaussians

SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenes

• Homepage: https://yihua7.github.io/SC-GS-web/
• Paper: https://arxiv.org/abs/2312.14937
• Code: https://github.com/yihua7/SC-GS

Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesis

• Homepage: https://oppo-us-research.github.io/SpacetimeGaussians-website/
• Paper: https://arxiv.org/abs/2312.16812
• Code: https://github.com/oppo-us-research/SpacetimeGaussians

DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization

• Homepage: https://fictionarry.github.io/DNGaussian/
• Paper: https://arxiv.org/abs/2403.06912
• Code: https://github.com/Fictionarry/DNGaussian

4D Gaussian Splatting for Real-Time Dynamic Scene Rendering

• Paper: https://arxiv.org/abs/2310.08528
• Code: https://github.com/hustvl/4DGaussians

GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models

• Paper: https://arxiv.org/abs/2310.08529
• Code: https://github.com/hustvl/GaussianDreamer

Avatars

GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussians

• Paper: https://arxiv.org/abs/2312.02134
• Code: https://github.com/huliangxiao/GaussianAvatar

Real-Time Simulated Avatar from Head-Mounted Sensors

• Homepage: https://www.zhengyiluo.com/SimXR/
• Paper: https://arxiv.org/abs/2403.06862

Backbone

RepViT: Revisiting Mobile CNN From ViT Perspective

• Paper: https://arxiv.org/abs/2307.09283
• Code: https://github.com/THU-MIG/RepViT

TransNeXt: Robust Foveal Visual Perception for Vision Transformers

• Paper: https://arxiv.org/abs/2311.17132
• Code: https://github.com/DaiShiResearch/TransNeXt

CLIP

Alpha-CLIP: A CLIP Model Focusing on Wherever You Want

• Paper: https://arxiv.org/abs/2312.03818
• Code: https://github.com/SunzeY/AlphaCLIP

FairCLIP: Harnessing Fairness in Vision-Language Learning

• Paper: https://arxiv.org/abs/2403.19949
• Code: https://github.com/Harvard-Ophthalmology-AI-Lab/FairCLIP

MAE

Embodied AI

EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI

• Homepage: https://tai-wang.github.io/embodiedscan/
• Paper: https://arxiv.org/abs/2312.16170
• Code: https://github.com/OpenRobotLab/EmbodiedScan

MP5: A Multi-modal Open-ended Embodied System in Minecraft via Active Perception

• Homepage: https://iranqin.github.io/MP5.github.io/
• Paper: https://arxiv.org/abs/2312.07472
• Code: https://github.com/IranQin/MP5

LEMON: Learning 3D Human-Object Interaction Relation from 2D Images

• Paper: https://arxiv.org/abs/2312.08963
• Code: https://github.com/yyvhang/lemon_3d

GAN

OCR

An Empirical Study of Scaling Law for OCR

• Paper: https://arxiv.org/abs/2401.00028
• Code: https://github.com/large-ocr-model/large-ocr-model.github.io

ODM: A Text-Image Further Alignment Pre-training Approach for Scene Text Detection and Spotting

• Paper: https://arxiv.org/abs/2403.00303
• Code: https://github.com/PriNing/ODM

NeRF

PIE-NeRF🍕: Physics-based Interactive Elastodynamics with NeRF

• Paper: https://arxiv.org/abs/2311.13099
• Code: https://github.com/FYTalon/pienerf/

DETR

DETRs Beat YOLOs on Real-time Object Detection

• Paper: https://arxiv.org/abs/2304.08069
• Code: https://github.com/lyuwenyu/RT-DETR

Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

• Paper: https://arxiv.org/abs/2403.16131
• Code: https://github.com/xiuqhou/Salience-DETR

Prompt

多模态大语言模型(MLLM)

mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration

• Paper: https://arxiv.org/abs/2311.04257
• Code: https://github.com/X-PLUG/mPLUG-Owl/tree/main/mPLUG-Owl2

Link-Context Learning for Multimodal LLMs

• Paper: https://arxiv.org/abs/2308.07891
• Code: https://github.com/isekai-portal/Link-Context-Learning/tree/main

OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation

• Paper: https://arxiv.org/abs/2311.17911
• Code: https://github.com/shikiw/OPERA

Making Large Multimodal Models Understand Arbitrary Visual Prompts

• Homepage: https://vip-llava.github.io/
• Paper: https://arxiv.org/abs/2312.00784

Pink: Unveiling the power of referential comprehension for multi-modal llms

• Paper: https://arxiv.org/abs/2310.00582
• Code: https://github.com/SY-Xuan/Pink

Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding

• Paper: https://arxiv.org/abs/2311.08046
• Code: https://github.com/PKU-YuanGroup/Chat-UniVi

OneLLM: One Framework to Align All Modalities with Language

• Paper: https://arxiv.org/abs/2312.03700
• Code: https://github.com/csuhan/OneLLM

大语言模型(LLM)

VTimeLLM: Empower LLM to Grasp Video Moments

• Paper: https://arxiv.org/abs/2311.18445
• Code: https://github.com/huangb23/VTimeLLM

NAS

ReID(重识别)

Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

• Paper: https://arxiv.org/abs/2403.10254
• Code: https://github.com/924973292/EDITOR

Noisy-Correspondence Learning for Text-to-Image Person Re-identification

• Paper: https://arxiv.org/abs/2308.09911

• Code : https://github.com/QinYang79/RDE

扩散模型(Diffusion Models)

InstanceDiffusion: Instance-level Control for Image Generation

• Homepage: https://people.eecs.berkeley.edu/~xdwang/projects/InstDiff/

• Paper: https://arxiv.org/abs/2402.03290

• Code: https://github.com/frank-xwang/InstanceDiffusion

Residual Denoising Diffusion Models

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/nachifur/RDDM

DeepCache: Accelerating Diffusion Models for Free

• Paper: https://arxiv.org/abs/2312.00858
• Code: https://github.com/horseee/DeepCache

DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations

• Homepage: https://tianhao-qi.github.io/DEADiff/

• Paper: https://arxiv.org/abs/2403.06951

• Code: https://github.com/Tianhao-Qi/DEADiff_code

SVGDreamer: Text Guided SVG Generation with Diffusion Model

• Paper: https://arxiv.org/abs/2312.16476
• Code: https://ximinng.github.io/SVGDreamer-project/

InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model

• Paper: https://arxiv.org/abs/2312.05849
• Code: https://github.com/jiuntian/interactdiffusion

MMA-Diffusion: MultiModal Attack on Diffusion Models

• Paper: https://arxiv.org/abs/2311.17516
• Code: https://github.com/yangyijune/MMA-Diffusion

VMC: Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models

• Homeoage: https://video-motion-customization.github.io/
• Paper: https://arxiv.org/abs/2312.00845
• Code: https://github.com/HyeonHo99/Video-Motion-Customization

Vision Transformer

TransNeXt: Robust Foveal Visual Perception for Vision Transformers

• Paper: https://arxiv.org/abs/2311.17132
• Code: https://github.com/DaiShiResearch/TransNeXt

RepViT: Revisiting Mobile CNN From ViT Perspective

• Paper: https://arxiv.org/abs/2307.09283
• Code: https://github.com/THU-MIG/RepViT

A General and Efficient Training for Transformer via Token Expansion

• Paper: https://arxiv.org/abs/2404.00672
• Code: https://github.com/Osilly/TokenExpansion

视觉和语言(Vision-Language)

PromptKD: Unsupervised Prompt Distillation for Vision-Language Models

• Paper: https://arxiv.org/abs/2403.02781
• Code: https://github.com/zhengli97/PromptKD

FairCLIP: Harnessing Fairness in Vision-Language Learning

• Paper: https://arxiv.org/abs/2403.19949
• Code: https://github.com/Harvard-Ophthalmology-AI-Lab/FairCLIP

目标检测(Object Detection)

DETRs Beat YOLOs on Real-time Object Detection

• Paper: https://arxiv.org/abs/2304.08069
• Code: https://github.com/lyuwenyu/RT-DETR

Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation

• Paper: https://arxiv.org/abs/2312.01220
• Code: https://github.com/ZPDu/Boosting-Object-Detection-with-Zero-Shot-Day-Night-Domain-Adaptation

YOLO-World: Real-Time Open-Vocabulary Object Detection

• Paper: https://arxiv.org/abs/2401.17270
• Code: https://github.com/AILab-CVC/YOLO-World

Salience DETR: Enhancing Detection Transformer with Hierarchical Salience Filtering Refinement

• Paper: https://arxiv.org/abs/2403.16131
• Code: https://github.com/xiuqhou/Salience-DETR

异常检测(Anomaly Detection)

Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection

• Paper: https://arxiv.org/abs/2310.12790
• Code: https://github.com/mala-lab/AHL

目标跟踪(Object Tracking)

Delving into the Trajectory Long-tail Distribution for Muti-object Tracking

• Paper: https://arxiv.org/abs/2403.04700
• Code: https://github.com/chen-si-jia/Trajectory-Long-tail-Distribution-for-MOT

语义分割(Semantic Segmentation)

Stronger, Fewer, & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation

• Paper: https://arxiv.org/abs/2312.04265
• Code: https://github.com/w1oves/Rein

SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation

• Paper: https://arxiv.org/abs/2311.15537
• Code: https://github.com/xb534/SED

医学图像(Medical Image)

Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology

• Paper: https://arxiv.org/abs/2402.17228
• Code: https://github.com/DearCaat/RRT-MIL

VoCo: A Simple-yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis

• Paper: https://arxiv.org/abs/2402.17300
• Code: https://github.com/Luffy03/VoCo

ChAda-ViT : Channel Adaptive Attention for Joint Representation Learning of Heterogeneous Microscopy Images

• Paper: https://arxiv.org/abs/2311.15264
• Code: https://github.com/nicoboou/chada_vit

医学图像分割(Medical Image Segmentation)

自动驾驶(Autonomous Driving)

UniPAD: A Universal Pre-training Paradigm for Autonomous Driving

• Paper: https://arxiv.org/abs/2310.08370
• Code: https://github.com/Nightmare-n/UniPAD

Cam4DOcc: Benchmark for Camera-Only 4D Occupancy Forecasting in Autonomous Driving Applications

• Paper: https://arxiv.org/abs/2311.17663
• Code: https://github.com/haomo-ai/Cam4DOcc

Memory-based Adapters for Online 3D Scene Perception

• Paper: https://arxiv.org/abs/2403.06974
• Code: https://github.com/xuxw98/Online3D

Symphonize 3D Semantic Scene Completion with Contextual Instance Queries

• Paper: https://arxiv.org/abs/2306.15670
• Code: https://github.com/hustvl/Symphonies

A Real-world Large-scale Dataset for Roadside Cooperative Perception

• Paper: https://arxiv.org/abs/2403.10145
• Code: https://github.com/AIR-THU/DAIR-RCooper

Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving

• Paper: https://arxiv.org/abs/2403.07535
• Code: https://github.com/Junda24/AFNet

Traffic Scene Parsing through the TSP6K Dataset

• Paper: https://arxiv.org/pdf/2303.02835.pdf
• Code: https://github.com/PengtaoJiang/TSP6K

3D点云(3D-Point-Cloud)

3D目标检测(3D Object Detection)

PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection

• Paper: https://arxiv.org/abs/2312.08371
• Code: https://github.com/kuanchihhuang/PTT

UniMODE: Unified Monocular 3D Object Detection

• Paper: https://arxiv.org/abs/2402.18573

3D语义分割(3D Semantic Segmentation)

图像编辑(Image Editing)

Edit One for All: Interactive Batch Image Editing

• Homepage: https://thaoshibe.github.io/edit-one-for-all
• Paper: https://arxiv.org/abs/2401.10219
• Code: https://github.com/thaoshibe/edit-one-for-all

视频编辑(Video Editing)

MaskINT: Video Editing via Interpolative Non-autoregressive Masked Transformers

• Homepage: https://maskint.github.io

• Paper: https://arxiv.org/abs/2312.12468

Low-level Vision

Residual Denoising Diffusion Models

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/nachifur/RDDM

Boosting Image Restoration via Priors from Pre-trained Models

• Paper: https://arxiv.org/abs/2403.06793

超分辨率(Super-Resolution)

SeD: Semantic-Aware Discriminator for Image Super-Resolution

• Paper: https://arxiv.org/abs/2402.19387
• Code: https://github.com/lbc12345/SeD

APISR: Anime Production Inspired Real-World Anime Super-Resolution

• Paper: https://arxiv.org/abs/2403.01598
• Code: https://github.com/Kiteretsu77/APISR

去噪(Denoising)

图像去噪(Image Denoising)

3D人体姿态估计(3D Human Pose Estimation)

Hourglass Tokenizer for Efficient Transformer-Based 3D Human Pose Estimation

• Paper: https://arxiv.org/abs/2311.12028
• Code: https://github.com/NationalGAILab/HoT

图像生成(Image Generation)

InstanceDiffusion: Instance-level Control for Image Generation

• Homepage: https://people.eecs.berkeley.edu/~xdwang/projects/InstDiff/

• Paper: https://arxiv.org/abs/2402.03290

• Code: https://github.com/frank-xwang/InstanceDiffusion

ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations

• Homepage: https://eclipse-t2i.vercel.app/

• Paper: https://arxiv.org/abs/2312.04655

• Code: https://github.com/eclipse-t2i/eclipse-inference

Instruct-Imagen: Image Generation with Multi-modal Instruction

• Paper: https://arxiv.org/abs/2401.01952

Residual Denoising Diffusion Models

• Paper: https://arxiv.org/abs/2308.13712
• Code: https://github.com/nachifur/RDDM

UniGS: Unified Representation for Image Generation and Segmentation

• Paper: https://arxiv.org/abs/2312.01985

Multi-Instance Generation Controller for Text-to-Image Synthesis

• Paper: https://arxiv.org/abs/2402.05408
• Code: https://github.com/limuloo/migc

SVGDreamer: Text Guided SVG Generation with Diffusion Model

• Paper: https://arxiv.org/abs/2312.16476
• Code: https://ximinng.github.io/SVGDreamer-project/

InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model

• Paper: https://arxiv.org/abs/2312.05849
• Code: https://github.com/jiuntian/interactdiffusion

Ranni: Taming Text-to-Image Diffusion for Accurate Prompt Following

• Paper: https://arxiv.org/abs/2311.17002
• Code: https://github.com/ali-vilab/Ranni

视频生成(Video Generation)

Vlogger: Make Your Dream A Vlog

• Paper: https://arxiv.org/abs/2401.09414
• Code: https://github.com/Vchitect/Vlogger

VBench: Comprehensive Benchmark Suite for Video Generative Models

• Homepage: https://vchitect.github.io/VBench-project/
• Paper: https://arxiv.org/abs/2311.17982
• Code: https://github.com/Vchitect/VBench

VMC: Video Motion Customization using Temporal Attention Adaption for Text-to-Video Diffusion Models

• Homeoage: https://video-motion-customization.github.io/
• Paper: https://arxiv.org/abs/2312.00845
• Code: https://github.com/HyeonHo99/Video-Motion-Customization

3D生成

CityDreamer: Compositional Generative Model of Unbounded 3D Cities

• Homepage: https://haozhexie.com/project/city-dreamer/
• Paper: https://arxiv.org/abs/2309.00610
• Code: https://github.com/hzxie/city-dreamer

LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching

• Paper: https://arxiv.org/abs/2311.11284
• Code: https://github.com/EnVision-Research/LucidDreamer

视频理解(Video Understanding)

MVBench: A Comprehensive Multi-modal Video Understanding Benchmark

• Paper: https://arxiv.org/abs/2311.17005
• Code: https://github.com/OpenGVLab/Ask-Anything/tree/main/video_chat2

知识蒸馏(Knowledge Distillation)

Logit Standardization in Knowledge Distillation

• Paper: https://arxiv.org/abs/2403.01427
• Code: https://github.com/sunshangquan/logit-standardization-KD

Efficient Dataset Distillation via Minimax Diffusion

• Paper: https://arxiv.org/abs/2311.15529
• Code: https://github.com/vimar-gu/MinimaxDiffusion

立体匹配(Stereo Matching)

Neural Markov Random Field for Stereo Matching

• Paper: https://arxiv.org/abs/2403.11193
• Code: https://github.com/aeolusguan/NMRF

场景图生成(Scene Graph Generation)

HiKER-SGG: Hierarchical Knowledge Enhanced Robust Scene Graph Generation

• Homepage: https://zhangce01.github.io/HiKER-SGG/
• Paper : https://arxiv.org/abs/2403.12033
• Code: https://github.com/zhangce01/HiKER-SGG

视频质量评价(Video Quality Assessment)

KVQ: Kaleidoscope Video Quality Assessment for Short-form Videos

• Homepage: https://lixinustc.github.io/projects/KVQ/

• Paper: https://arxiv.org/abs/2402.07220

• Code: https://github.com/lixinustc/KVQ-Challenge-CVPR-NTIRE2024

数据集(Datasets)

A Real-world Large-scale Dataset for Roadside Cooperative Perception

• Paper: https://arxiv.org/abs/2403.10145
• Code: https://github.com/AIR-THU/DAIR-RCooper

Traffic Scene Parsing through the TSP6K Dataset

• Paper: https://arxiv.org/pdf/2303.02835.pdf
• Code: https://github.com/PengtaoJiang/TSP6K

其他(Others)

Object Recognition as Next Token Prediction

• Paper: https://arxiv.org/abs/2312.02142
• Code: https://github.com/kaiyuyue/nxtp

ParameterNet: Parameters Are All You Need for Large-scale Visual Pretraining of Mobile Networks

• Paper: https://arxiv.org/abs/2306.14525
• Code: https://parameternet.github.io/

Seamless Human Motion Composition with Blended Positional Encodings

• Paper: https://arxiv.org/abs/2402.15509
• Code: https://github.com/BarqueroGerman/FlowMDM

LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning

• Homepage: https://ll3da.github.io/

• Paper: https://arxiv.org/abs/2311.18651

• Code: https://github.com/Open3DA/LL3DA

CLOVA: A Closed-LOop Visual Assistant with Tool Usage and Update

• Homepage: https://clova-tool.github.io/
• Paper: https://arxiv.org/abs/2312.10908

MoMask: Generative Masked Modeling of 3D Human Motions

• Paper: https://arxiv.org/abs/2312.00063
• Code: https://github.com/EricGuo5513/momask-codes

Amodal Ground Truth and Completion in the Wild

• Homepage: https://www.robots.ox.ac.uk/~vgg/research/amodal/
• Paper: https://arxiv.org/abs/2312.17247
• Code: https://github.com/Championchess/Amodal-Completion-in-the-Wild

Improved Visual Grounding through Self-Consistent Explanations

• Paper: https://arxiv.org/abs/2312.04554
• Code: https://github.com/uvavision/SelfEQ

ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object

• Homepage: https://chenshuang-zhang.github.io/imagenet_d/
• Paper: https://arxiv.org/abs/2403.18775
• Code: https://github.com/chenshuang-zhang/imagenet_d

Learning from Synthetic Human Group Activities

• Homepage: https://cjerry1243.github.io/M3Act/
• Paper https://arxiv.org/abs/2306.16772
• Code: https://github.com/cjerry1243/M3Act

A Cross-Subject Brain Decoding Framework

• Homepage: https://littlepure2333.github.io/MindBridge/
• Paper: https://arxiv.org/abs/2404.07850
• Code: https://github.com/littlepure2333/MindBridge

Multi-Task Dense Prediction via Mixture of Low-Rank Experts

• Paper : https://arxiv.org/abs/2403.17749
• Code: https://github.com/YuqiYang213/MLoRE

Contrastive Mean-Shift Learning for Generalized Category Discovery

• Homepage: https://postech-cvlab.github.io/cms/
• Paper: https://arxiv.org/abs/2404.09451
• Code: https://github.com/sua-choi/CMS

cvpr2024-papers-with-code's Issues

添加一篇GAN相关的CVPR 2020 Oral Paper

PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer
(CVPR 2020 Oral)

paper: https://arxiv.org/abs/1909.06956
code: https://github.com/wtjiang98/PSGAN

神经网络剪枝文章

论文标题：Hrank: Filter Pruning using High-Rank Feature Map
论文：http://arxiv.org/abs/2002.10179
代码：https://github.com/lmbxmu/HRank

添加一篇对抗样本论文

Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction
论文地址：https://openaccess.thecvf.com/content_CVPR_2020/papers/Lu_Enhancing_Cross-Task_Black-Box_Transferability_of_Adversarial_Examples_With_Dispersion_Reduction_CVPR_2020_paper.pdf
代码地址：https://github.com/erbloo/dr_cvpr20

添加一篇video captioning的文章

Syntax-Aware Action Targeting for Video Captioning
论文: http://openaccess.thecvf.com/content_CVPR_2020/papers/Zheng_Syntax-Aware_Action_Targeting_for_Video_Captioning_CVPR_2020_paper.pdf
代码: https://github.com/SydCaption/SAAT
谢谢~

[CVPR2020] EfficientDet: Scalable and Efficient Object Detection

方向：目标检测
题目：EfficientDet: Scalable and Efficient Object Detection
ArXiv: https://arxiv.org/abs/1911.09070
GitHub: https://github.com/google/automl/tree/master/efficientdet

无意间发现的很不错的文章，好像这里漏掉了

Point Cloud Segmentation

Hi @amusi, could you update this paper (CVPR2020)

"PointASNL: Robust Point Clouds Processing using Nonlocal Neural Networks with Adaptive Sampling"

paper: https://arxiv.org/pdf/2003.00492.pdf
code: https://github.com/yanx27/PointASNL

[Code Link Changed]: Could you please update it?

Hi, our open-source code has a new link, and we will release the code in the next week. Could you please update the information? Thank you very much!

3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior

Paper Link：https://arxiv.org/abs/2003.14052
Code Link：https://github.com/charlesCXK/TorchSSC

新增模型压缩相关文章一篇，感谢

模型压缩（二值神经网络）相关文章一篇，已中
论文标题：Forward and Backward Information Retention for Accurate Binary Neural Networks
论文arXiv链接：https://arxiv.org/abs/1909.10788
代码：https://github.com/htqin/IR-Net/

添加一篇视频插帧文章

FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation

论文: http://openaccess.thecvf.com/content_CVPR_2020/html/Gui_FeatureFlow_Robust_Video_Interpolation_via_Structure-to-Texture_Generation_CVPR_2020_paper.html

代码：
https://github.com/CM-BF/FeatureFlow

谢谢！

添加几篇文章

1. TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style
   数据集，三维重建
   paper:
   http://openaccess.thecvf.com/content_CVPR_2020/papers/Patel_TailorNet_Predicting_Clothing_in_3D_as_a_Function_of_Human_CVPR_2020_paper.pdf
   code：
   https://github.com/chaitanya100100/TailorNet
   数据集：
   https://github.com/zycliao/TailorNet_dataset

2. Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion
   三维重建
   paper:
   http://openaccess.thecvf.com/content_CVPR_2020/papers/Chibane_Implicit_Functions_in_Feature_Space_for_3D_Shape_Reconstruction_and_CVPR_2020_paper.pdf
   code:
   https://github.com/jchibane/if-net

3. Learning to Transfer Texture from Clothing Images to 3D Humans
   三维重建
   paper:
   http://openaccess.thecvf.com/content_CVPR_2020/papers/Mir_Learning_to_Transfer_Texture_From_Clothing_Images_to_3D_Humans_CVPR_2020_paper.pdf
   code:
   https://github.com/aymenmir1/pix2surf

视频超分辨率论文重复

有两个 Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

有其他顶会的开源代码整理吗？

您好，感谢做了非常不错的整理，这个是2020CVPR的开源代码整理，像2019年的顶会您有做开源代码的整理吗？谢谢

Reqest for adding a new paper

Title: Oops! Predicting Unintentional Action in Video
Paper: https://arxiv.org/abs/1911.11206
Code: https://github.com/cvlab-columbia/oops
Dataset: https://oops.cs.columbia.edu/data/
Website: https://oops.cs.columbia.edu/

Thank you!

添加一篇行为轨迹预测的paper

The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

论文: https://arxiv.org/abs/1912.06445
代码: https://github.com/JunweiLiang/Multiverse
数据集: https://next.cs.cmu.edu/multiverse/

谢谢！

CVPR2020 Polarized Reflection Removal

用偏振相机做去反光，后续会开源代码以及数据集。

project website: https://leichenyang.weebly.com/project-polarized.html
code: https://github.com/ChenyangLEI/CVPR2020-Polarized-Reflection-Removal-with-Perfect-Alignment

非常感谢！

添加一篇GAN用于representation learning的文章 "Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning"

Full-text link: https://arxiv.org/abs/1912.01899
code link: https://github.com/SsGood/DBGAN

Deep Learning相关

希望能添加一下我们的文章（已中）：

标题：Filter Grafting for Deep Neural Networks

论文链接：https://arxiv.org/abs/2001.05868
代码链接：https://github.com/fxmeng/filter-grafting
论文解读：https://www.zhihu.com/question/372070853/answer/1041569335

谢谢～

Request for adding a new paper on Domain Generalization

Learning to Learn Single Domain Generalization

Paper: https://arxiv.org/abs/2003.13216

Code: https://github.com/joffery/M-ADA

Thanks!

添加一篇目标检测论文

Noise-Aware Fully Webly Supervised Object Detection

论文地址：http://openaccess.thecvf.com/content_CVPR_2020/html/Shen_Noise-Aware_Fully_Webly_Supervised_Object_Detection_CVPR_2020_paper.html

代码地址：https://github.com/shenyunhang/NA-fWebSOD/

谢谢

增加一篇新论文：3D点云配准

3D点云配准

Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences
论文：https://arxiv.org/abs/2005.01014
代码：https://github.com/XiaoshuiHuang/fmr

please kindly add HOReID

Thanks for your awesome work.
please kindly add the following Re-ID work.

Title: High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification
Paper: http://openaccess.thecvf.com/content_CVPR_2020/html/Wang_High-Order_Information_Matters_Learning_Relation_and_Topology_for_Occluded_Person_CVPR_2020_paper.html
Code: https://github.com/wangguanan/HOReID

添加一篇无监督光流估计文章

Learning by Analogy: Reliable Supervision from Transformations for Unsupervised Optical Flow Estimation
论文: https://arxiv.org/abs/2003.13045
代码: https://github.com/lliuz/ARFlow
谢谢！

Request for adding a new paper

Paper Title: Evade Deep Image Retrieval by Stashing Private Images in the Hash Space

Paper Address: http://openaccess.thecvf.com/content_CVPR_2020/html/Xiao_Evade_Deep_Image_Retrieval_by_Stashing_Private_Images_in_the_CVPR_2020_paper.html

Code Address: https://github.com/sugarruy/hashstash

Thanks!

融合惯导和多视角图像的3D人体姿态估计

Fusing Wearable IMUs with Multi-View Images for Human Pose Estimation: A Geometric Approach (CVPR 2020)

project page: https://www.zhe-zhang.com/cvpr2020
code framework：pytorch
SOTA experimental results on TotalCapture Dataset

添加一篇场景文字检测文章

ContourNet: Taking a Further Step Toward Accurate Arbitrary-Shaped Scene Text Detection
论文地址：http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_ContourNet_Taking_a_Further_Step_Toward_Accurate_Arbitrary-Shaped_Scene_Text_CVPR_2020_paper.pdf
代码地址：https://github.com/wangyuxin87/ContourNet

Request for adding a new oral paper

Interpretable and Accurate Fine-grained Recognition via Region Grouping (CVPR 2020, Oral)

Paper: https://arxiv.org/pdf/2005.10411.pdf
Code: https://github.com/zxhuang1698/interpretability-by-parts
Category: 可解释性/图像分类/其他

Thanks!

增加人脸重建论文FaceScape

见PR: #14

可否添加代码库时，附上平台，如TensorFlow、PyTorch等

thx

添加一篇HOI的paper

PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection
https://arxiv.org/pdf/1912.12898
https://github.com/YueLiao/PPDM

Request for adding a new paper

Title: An Efficient PointLSTM for Point Clouds Based Gesture Recognition
Paper: http://openaccess.thecvf.com/content_CVPR_2020/html/Min_An_Efficient_PointLSTM_for_Point_Clouds_Based_Gesture_Recognition_CVPR_2020_paper.html
Code: https://github.com/Blueprintf/pointlstm-gesture-recognition-pytorch

Thank you!

[CVPR2020] Learning Meta Face Recognition in Unseen Domains

方向：跨域人脸识别
论文标题：Learning Meta Face Recognition in Unseen Domains
论文：ArXiv or here
协议 & 评测代码：https://github.com/cleardusk/MFR （更新中）
软文：https://mp.weixin.qq.com/s/YZoEnjpnlvb90qSI3xdJqQ

如能添加，非常感谢！

添加一篇3D目标检测的文章

Full-text link: http://openaccess.thecvf.com/content_CVPR_2020/papers/Peng_IDA-3D_Instance-Depth-Aware_3D_Object_Detection_From_Stereo_Vision_for_Autonomous_CVPR_2020_paper.pdf
code link: https://github.com/swords123/IDA-3D

添加一篇线框解析的文章

Holistically-Attracted Wireframe Parser

Fulltext: http://openaccess.thecvf.com/content_CVPR_2020/html/Xue_Holistically-Attracted_Wireframe_Parsing_CVPR_2020_paper.html

Code: https://github.com/cherubicXN/hawp

Please add our paper on deep learning

title: Dynamic Hierarchical Mimicking Towards Consistent Optimization Objectives
paper: https://arxiv.org/abs/2003.10739
code: https://github.com/d-li14/DHM

Please add our paper about deep learning

Title: Deep Image Spatial Transformation for person image generation
Code: https://github.com/RenYurui/Global-Flow-Local-Attention
Paper: https://arxiv.org/abs/2003.00696

风格迁移论文一篇

论文标题："Diversified Arbitrary Style Transfer via Deep Feature Perturbation"
论文链接：https://arxiv.org/abs/1909.08223
代码：https://github.com/EndyWon/Deep-Feature-Perturbation

感谢！

添加一篇3D人体姿态估计论文

Cascaded Deep Monocular 3D Human Pose Estimation With Evolutionary Training Data
论文地址：https://arxiv.org/abs/2006.07778
代码地址：https://github.com/Nicholasli1995/EvoSkeleton

Superglue isn't here

While the training isn't open sourced, their pre-trained networks are

Paper
Code

目标跟踪方面论文两篇

Kenan Dai, Yunhua Zhang, Dong Wang, Jianhua Li, Huchuan Lu, Xiaoyun Yang, High-Performance Long-Term Tracking with Meta-Updater, CVPR2020
论文：https://arxiv.org/abs/2004.00305
代码：https://github.com/Daikenan/LTMU

Bin Yan, Dong Wang, Huchuan Lu, Xiaoyun Yang, Cooling-Shrinking Attack: Blinding the Tracker with Imperceptible Noises, CVPR2020
论文：https://arxiv.org/abs/2003.09595
代码：https://github.com/MasterBin-IIAU/CSA

目前已中，希望可以添加

方向：视频增强（视频去模糊）
论文标题：Cascaded Deep Video Deblurring Using Temporal Sharpness Prior
论文：准备中
code：https://github.com/csbhr/CDVD-TSP
project page：https://csbhr.github.io/projects/cdvd-tsp/index.html

如能添加，非常感谢！

[语义场景补全] 论文1篇

3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior

论文：https://arxiv.org/abs/2003.14052
代码：https://github.com/charlesCXK/3D-SketchAware-SSC

Thank you very much !

添加一篇基于骨架的非监督行为识别

PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition
论文: https://arxiv.org/abs/1911.12409
代码: https://github.com/shlizee/Predict-Cluster
谢谢！

添加一篇GAN论文

Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation（NICE-GAN）
论文地址：http://openaccess.thecvf.com/content_CVPR_2020/html/Chen_Reusing_Discriminators_for_Encoding_Towards_Unsupervised_Image-to-Image_Translation_CVPR_2020_paper.html
代码地址：https://github.com/alpc91/NICE-GAN-pytorch

求添加一下我们的文章Rethinking Performance Estimation in Neural Architecture Search

目前已中
论文标题：Rethinking Performance Estimation in Neural Architecture Search
论文：准备中
代码：https://github.com/zhengxiawu/rethinking_performance_estimation_in_NAS
解读：https://www.zhihu.com/question/372070853/answer/1035234510

如能添加，非常感谢！

添加一篇视频超分辨率和一篇视频插值的文章

视频超分辨率：

TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution

论文：https://arxiv.org/abs/1812.02898
代码：https://github.com/YapengTian/TDAN-VSR-CVPR-2020

视频插值:

Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

论文：https://arxiv.org/abs/2002.11616
代码：https://github.com/Mukosame/Zooming-Slow-Mo-CVPR-2020

图像分类

代码： https://github.com/ildoonet/spatially-attentive-output-layer this link reports 404. do you have the code? hope your replay

对抗样本CVPR2020文章一篇

对抗样本（Adversarial Examples）相关文章一篇，已中
论文标题：Zhao, Zhengyu, Zhuoran Liu, and Martha Larson. "Towards Large yet Imperceptible Adversarial Image Perturbations with Perceptual Color Distance."
论文arXiv链接：https://arxiv.org/abs/1911.02466
代码：https://github.com/ZhengyuZhao/PerC-Adversarial

望添加，多谢~

添加一篇3D目标检测论文

Structure Aware Single-stage 3D Object Detection from Point Cloud

论文地址：http://openaccess.thecvf.com/content_CVPR_2020/html/He_Structure_Aware_Single-Stage_3D_Object_Detection_From_Point_Cloud_CVPR_2020_paper.html

代码地址：https://github.com/skyhehe123/SA-SSD

谢谢

Class Add

Can you add a new class about Face Age Estimation?

3D Reconstruction Paper

Hi, I saw this CVPR 2020 paper which has nice code on github: https://github.com/autonomousvision/differentiable_volumetric_rendering