A paper list of some recent Transformer-based CV works. If you find some ignored papers, please open issues or pull requests.
**Last updated: 2023/09/04
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(arXiv 2023.07) A Survey of Techniques for Optimizing Transformer Inference. [Paper]
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(arXiv 2023.07) Transformers in Reinforcement Learning: A Survey. [Paper]
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(arXiv 2023.07) Vision Language Transformers: A Survey. [Paper]
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(arXiv 2023.06) 2D Object Detection with Transformers: A Review. [Paper], [Awesome]
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(arXiv 2023.05) Vision Transformers for Mobile Applications: A Short Survey. [Paper]
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(arXiv 2023.05) A survey of the Vision Transformers and its CNN-Transformer based Variants. [Paper]
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(arXiv 2023.05) Semantic Segmentation using Vision Transformers: A survey. [Paper]
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(arXiv 2023.04) Transformer-based models and hardware acceleration analysis in autonomous driving: A survey. [Paper]
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(arXiv 2023.04) Transformer-Based Visual Segmentation: A Survey. [Paper], [Awesome]
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(arXiv 2023.02) Transformer-based Generative Adversarial Networks in Computer Vision: A Comprehensive Survey. [Paper]
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(arXiv 2023.02) A Survey on Efficient Training of Transformers. [Paper]
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(arXiv 2023.01) Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review. [Paper], [Awesome]
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(arXiv 2022.11) Vision Transformers in Medical Imaging: A Review. [Paper]
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(arXiv 2022.11) A Comprehensive Survey of Transformers for Computer Vision. [Paper]
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(arXiv 2022.09) A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective. [Paper]
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(arXiv 2022.09) Vision Transformers for Action Recognition: A Survey. [Paper]
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(arXiv 2022.09) Transformers in Remote Sensing: A Survey. [Paper], [Awesome]
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(arXiv 2022.08) Medical image analysis based on transformer: A Review. [Paper]
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(arXiv 2022.08) 3D Vision with Transformers: A Survey. [Paper], [Awesome]
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(arXiv 2022.05) Multimodal Learning with Transformers: A Survey. [Paper]
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(arXiv 2022.05) Transformers in 3D Point Clouds: A Survey. [Paper]
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(arXiv 2022.03) Vision Transformers in Medical Computer Vision - A Contemplative Retrospection. [Paper]
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(arXiv 2022.03) Transformers Meet Visual Learning Understanding: A Comprehensive Review. [Paper]
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(arXiv 2022.03) Recent Advances in Vision Transformer: A Survey and Outlook of Recent Work. [Paper]
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(arXiv 2022.02) Transformers in Medical Image Analysis: A Review. [Paper]
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(arXiv 2022.01) Transformers in Medical Imaging: A Survey. [Paper], [Awesome]
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(arXiv 2022.01) A Comprehensive Study of Vision Transformers on Dense Prediction Tasks. [Paper]
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(arXiv 2022.01) Video Transformers: A Survey. [Paper]
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(arXiv 2021.11) A Survey of Visual Transformers. [Paper]
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(arXiv 2021.09) Survey: Transformer based Video-Language Pre-training. [Paper]
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(arXiv 2021.03) Multi-modal Motion Prediction with Stacked Transformers. [Paper], [Code]
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(arXiv 2021.03) Perspectives and Prospects on Transformer Architecture for Cross-Modal Tasks with Language and Vision. [Paper]
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(arXiv 2020.09) Efficient Transformers: A Survey. [Paper]
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(arXiv 2020.01) Transformers in Vision: A Survey. [Paper]
- (CVPR'20) Speech2Action: Cross-modal Supervision for Action Recognition, [Paper]
- (arXiv 2021.01) Trear: Transformer-based RGB-D Egocentric Action Recognition, [Paper]
- (arXiv 2021.02) Relaxed Transformer Decoders for Direct Action Proposal Generation, [Paper], [Code]
- (arXiv 2021.04) TubeR: Tube-Transformer for Action Detection, [Paper]
- (arXiv 2021.04) Few-Shot Transformation of Common Actions into Time and Space, [Paper]
- (arXiv 2021.05) Temporal Action Proposal Generation with Transformers, [Paper]
- (arXiv 2021.06) End-to-end Temporal Action Detection with Transformer, [Paper], [Code]
- (arXiv 2021.06) OadTR: Online Action Detection with Transformers, [Paper], [Code]
- (arXiv 2021.07) Action Transformer: A Self-Attention Model for Short-Time Human Action Recognition, [Paper]
- (arXiv 2021.07) VideoLightFormer: Lightweight Action Recognition using Transformers, [Paper]
- (arXiv 2021.07) Long Short-Term Transformer for Online Action Detection, [Paper]
- (arXiv 2021.07) STAR: Sparse Transformer-based Action Recognition, [Paper], [Code]
- (arXiv 2021.08) Shifted Chunk Transformer for Spatio-Temporal Representational Learning, [Paper]
- (arXiv 2021.08) GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer, [Paper], [Code]
- (arXiv 2021.09) GCsT: Graph Convolutional Skeleton Transformer for Action Recognition, [Paper], [Code]
- (arXiv 2021.10) Lightweight Transformer in Federated Setting for Human Activity Recognition, [Paper]
- (arXiv 2021.10) ASFormer: Transformer for Action Segmentation, [Paper], [Code]
- (arXiv 2021.10) Few-Shot Temporal Action Localization with Query Adaptive Transformer, [Paper], [Code]
- (arXiv 2021.10) IIP-Transformer: Intra-Inter-Part Transformer for Skeleton-Based Action Recognition, [Paper], [Code]
- (arXiv 2021.11) Evaluating Transformers for Lightweight Action Recognition, [Paper]
- (arXiv 2021.12) MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection, [Paper]
- (arXiv 2021.12) Co-training Transformer with Videos and Images Improves Action Recognition, [Paper]
- (arXiv 2021.12) Temporal Transformer Networks with Self-Supervision for Action Recognition, [Paper]
- (arXiv 2022.01) Spatio-Temporal Tuples Transformer for Skeleton-Based Action Recognition, [Paper], [Code]
- (arXiv 2022.01) Transformers in Action:Weakly Supervised Action Segmentation, [Paper]
- (arXiv 2022.02) ActionFormer: Localizing Moments of Actions with Transformers, [Paper], [Code]
- (arXiv 2022.03) Multi-View Fusion Transformer for Sensor-Based Human Activity Recognition, [Paper]
- (arXiv 2022.03) TransDARC: Transformer-based Driver Activity Recognition with Latent Space Feature Calibration, [Paper], [Code]
- (arXiv 2022.03) Zero-Shot Action Recognition with Transformer-based Video Semantic Embedding, [Paper]
- (arXiv 2022.03) LocATe: End-to-end Localization of Actions in 3D with Transformers, [Paper]
- (arXiv 2022.03) DirecFormer: A Directed Attention in Transformer Approach to Robust Action Recognition, [Paper], [Code]
- (arXiv 2022.03) Multi-label Transformer for Action Unit Detection, [Paper]
- (arXiv 2022.04) Vision Transformer with Cross-attention by Temporal Shift for Efficient Action Recognition, [Paper]
- (arXiv 2022.04) TALLFormer: Temporal Action Localization with Long-memory Transformer, [Paper], [Code]
- (arXiv 2022.04) TransRAC: Encoding Multi-scale Temporal Correlation with Transformers for Repetitive Action Counting, [Paper], [Code]
- (arXiv 2022.04) Detector-Free Weakly Supervised Group Activity Recognition, [Paper], [Code]
- (arXiv 2022.05) Cross-modal Representation Learning for Zero-shot Action Recognition, [Paper], [Code]
- (arXiv 2022.05) Entity-aware and Motion-aware Transformers for Language-driven Action Localization in Videos, [Paper], [Code]
- (arXiv 2022.05) Cross-subject Action Unit Detection with Meta Learning and Transformer-based Relation Modeling, [Paper]
- (arXiv 2022.05) Cross-Enhancement Transformer for Action Segmentation, [Paper]
- (arXiv 2022.05) Efficient U-Transformer with Boundary-Aware Loss for Action Segmentation, [Paper]
- (arXiv 2022.05) Future Transformer for Long-term Action Anticipation, [Paper], [Code]
- (arXiv 2022.06) One-stage Action Detection Transformer, [Paper]
- (arXiv 2022.06) Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition, [Paper]
- (arXiv 2022.07) Hunting Group Clues with Transformers for Social Group Activity Recognition, [Paper]
- (arXiv 2022.07) Global-local Motion Transformer for Unsupervised Skeleton-based Action Learning, [Paper],[Code]
- (arXiv 2022.07) Entry-Flipped Transformer for Inference and Prediction of Participant Behavior, [Paper],[Code]
- (arXiv 2022.07) Action Quality Assessment with Temporal Parsing Transformer, [Paper]
- (arXiv 2022.07) HTNet: Anchor-free Temporal Action Localization with Hierarchical Transformers, [Paper]
- (arXiv 2022.07) An Efficient Spatio-Temporal Pyramid Transformer for Action Detection, [Paper]
- (arXiv 2022.07) Action Quality Assessment using Transformers, [Paper]
- (arXiv 2022.07) Unsupervised Domain Adaptation for Video Transformers in Action Recognition, [Paper],[Code]
- (arXiv 2022.07) Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action Recognition, [Paper],[Code]
- (arXiv 2022.08) Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition, [Paper]
- (arXiv 2022.08) ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos, [Paper],[Code]
- (arXiv 2022.08) Adaptive Perception Transformer for Temporal Action Localization, [Paper],[Code]
- (arXiv 2022.08) A Circular Window-based Cascade Transformer for Online Action Detection, [Paper]
- (arXiv 2022.09) Self-Supervised Multimodal Fusion Transformer for Passive Activity Recognition, [Paper]
- (arXiv 2022.09) TASKED: Transformer-based Adversarial learning for human activity recognition using wearable sensors via Self-KnowledgE Distillation, [Paper]
- (arXiv 2022.09) Exploring Modulated Detection Transformer as a Tool for Action Recognition in Videos, [Paper]
- (arXiv 2022.09) Lightweight Transformers for Human Activity Recognition on Mobile Devices, [Paper]
- (arXiv 2022.09) Multi-dataset Training of Transformers for Robust Action Recognition, [Paper],[Code]
- (arXiv 2022.10) Focal and Global Spatial-Temporal Transformer for Skeleton-based Action Recognition, [Paper],[Code]
- (arXiv 2022.10) STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognition, [Paper]
- (arXiv 2022.10) Transformer-based Action recognition in hand-object interacting scenarios, [Paper]
- (arXiv 2022.10) Anticipative Feature Fusion Transformer for Multi-Modal Action Anticipation, [Paper]
- (arXiv 2022.10) Holistic Interaction Transformer Network for Action Detection, [Paper],[Code]
- (arXiv 2022.10) GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction, [Paper]
- (arXiv 2022.10) Hypergraph Transformer for Skeleton-based Action Recognition, [Paper]
- (arXiv 2022.11) SVFormer: Semi-supervised Video Transformer for Action Recognition, [Paper],[Code]
- (arXiv 2022.11) Interaction Visual Transformer for Egocentric Action Anticipation, [Paper],[Code]
- (arXiv 2023.02) Transformers in Action Recognition: A Review on Temporal Modeling, [Paper]
- (arXiv 2023.02) Video Action Recognition Collaborative Learning with Dynamics via PSO-ConvNet Transformer, [Paper],[Code]
- (arXiv 2023.02) Spatial-temporal Transformer-guided Diffusion based Data Augmentation for Efficient Skeleton-based Action Recognition, [Paper]
- (arXiv 2023.02) Temporal Segment Transformer for Action Segmentation, [Paper]
- (arXiv 2023.03) EgoViT: Pyramid Video Transformer for Egocentric Action Recognition, [Paper]
- (arXiv 2023.03) Vision Transformer for Action Units Detection, [Paper]
- (arXiv 2023.03) Group Activity Recognition using Self-supervised Approach of Spatiotemporal Transformers, [Paper]
- (arXiv 2023.03) 3Mformer: Multi-order Multi-mode Transformer for Skeletal Action Recognition, [Paper]
- (arXiv 2023.04) STMT: A Spatial-Temporal Mesh Transformer for MoCap-Based Action Recognition, [Paper],[Code]
- (arXiv 2023.04) End-to-End Spatio-Temporal Action Localisation with Video Transformers, [Paper]
- (arXiv 2023.05) Distilled Mid-Fusion Transformer Networks for Multi-Modal Human Activity Recognition, [Paper]
- (arXiv 2023.05) Multi-View Multi-Scale Driver Action Recognition with Vision Transformer, [Paper],[Code]
- (arXiv 2023.05) Enhancing Transformer Backbone for Egocentric Video Action Segmentation, [Paper],[Code]
- (arXiv 2023.05) A Multi-Modal Transformer Network for Action Detection, [Paper]
- (arXiv 2023.06) Optimizing ViViT Training: Time and Memory Reduction for Action Recognition, [Paper]
- (arXiv 2023.06) SpATr: MoCap 3D Human Action Recognition based on Spiral Auto-encoder and Transformer Network, [Paper]
- (arXiv 2023.07) Task-Specific Alignment and Multiple Level Transformer for Few-Shot Action Recognition, [Paper],[Code]
- (arXiv 2023.07) VS-TransGRU: A Novel Transformer-GRU-based Framework Enhanced by Visual-Semantic Fusion for Egocentric Action Anticipation, [Paper]
- (arXiv 2023.07) Multimodal Distillation for Egocentric Action Recognition, [Paper]
- (arXiv 2023.07) Human Action Recognition in Still Images Using ConViT, [Paper]
- (arXiv 2023.07) MSQNet: Actor-agnostic Action Recognition with Multi-modal Query, [Paper], [Code]
- (arXiv 2023.07) Event-based Vision for Early Prediction of Manipulation Actions, [Paper]
- (arXiv 2023.08) PAT: Position-Aware Transformer for Dense Multi-Label Action Detection, [Paper]
- (arXiv 2023.08) Seeing in Flowing: Adapting CLIP for Action Recognition with Motion Prompts Learning, [Paper]
- (arXiv 2023.08) MAiVAR-T: Multimodal Audio-image and Video Action Recognizer using Transformers, [Paper]
- (arXiv 2023.08) Memory-and-Anticipation Transformer for Online Action Understanding, [Paper], [Code]
- (arXiv 2023.08) Self-Feedback DETR for Temporal Action Detection, [Paper], [Code]
- (arXiv 2023.08) EventTransAct: A video transformer-based framework for Event-camera based action recognition, [Paper], [Code]
- (arXiv 2023.08) Topology-aware MLP for Skeleton-based Action Recognition, [Paper], [Code]
- (arXiv 2023.08) Prompt-enhanced Hierarchical Transformer Elevating Cardiopulmonary Resuscitation Instruction via Temporal Action Segmentation, [Paper]
- (arXiv 2022.06) Exploring Adversarial Attacks and Defenses in Vision Transformers trained with DINO, [Paper], [Code]
- (arXiv 2022.06) Backdoor Attacks on Vision Transformers, [Paper], [Code]
- (arXiv 2022.06) Defending Backdoor Attacks on Vision Transformer via Patch Processing, [Paper]
- (arXiv 2022.07) Towards Efficient Adversarial Training on Vision Transformers, [Paper]
- (arXiv 2022.08) Understanding Adversarial Robustness of Vision Transformers via Cauchy Problem, [Paper], [Code]
- (arXiv 2022.08) Analyzing Adversarial Robustness of Vision Transformers against Spatial and Spectral Attacks, [Paper]
- (arXiv 2023.01) Inference Time Evidences of Adversarial Attacks for Forensic on Transformers, [Paper]
- (arXiv 2023.03) Transferable Adversarial Attacks on Vision Transformers with Token Gradient Regularization, [Paper]
- (arXiv 2023.05) On enhancing the robustness of Vision Transformers: Defensive Diffusion, [Paper], [Code]
- (arXiv 2023.06) Pre-trained transformer for adversarial purification, [Paper]
- (arXiv 2023.07) Random Position Adversarial Patch for Vision Transformers, [Paper]
- (arXiv 2023.07) Enhanced Security against Adversarial Examples Using a Random Ensemble of Encrypted Vision Transformer Models, [Paper]
- (arXiv 2021.04) VT-ADL: A Vision Transformer Network for Image Anomaly Detection and Localization, [Paper]
- (arXiv 2021.04) Inpainting Transformer for Anomaly Detection, [Paper]
- (arXiv 2022.03) AnoViT: Unsupervised Anomaly Detection and Localization with Vision Transformer-based Encoder-Decoder, [Paper]
- (arXiv 2022.06) Anomaly detection in surveillance videos using transformer based attention model, [Paper], [Code]
- (arXiv 2022.06) Multi-Contextual Predictions with Vision Transformer for Video Anomaly Detection, [Paper]
- (arXiv 2022.08) HaloAE: An HaloNet based Local Transformer Auto-Encoder for Anomaly Detection and Localization, [Paper], [Code]
- (arXiv 2022.08) ADTR: Anomaly Detection Transformer with Feature Reconstruction, [Paper]
- (arXiv 2022.09) Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection, [Paper], [Code]
- (arXiv 2022.09) Anomaly Detection in Aerial Videos with Transformers, [Paper], [Code]
- (arXiv 2022.10) Masked Transformer for image Anomaly Localization, [Paper]
- (arXiv 2022.11) Generalizable Industrial Visual Anomaly Detection with Self-Induction Vision Transformer, [Paper]
- (arXiv 2023.03) Incremental Self-Supervised Learning Based on Transformer for Anomaly Detection and Localization, [Paper]
- (arXiv 2023.03) Unsupervised Anomaly Detection with Local-Sensitive VQVAE and Global-Sensitive Transformers, [Paper]
- (arXiv 2023.03) Visual Anomaly Detection via Dual-Attention Transformer and Discriminative Flow, [Paper]
- (arXiv 2023.05) Multiresolution Feature Guidance Based Transformer for Anomaly Detection, [Paper]
- (arXiv 2023.06) Efficient Anomaly Detection with Budget Annotation Using Semi-Supervised Residual Transformer, [Paper], [Code]
- (arXiv 2023.07) SelFormaly: Towards Task-Agnostic Unified Anomaly Detection, [Paper]
- (arXiv 2023.08) Patch-wise Auto-Encoder for Visual Anomaly Detection, [Paper]
- (arXiv 2021.01) Transformer for Image Quality Assessment, [Paper], [Code]
- (arXiv 2021.04) Perceptual Image Quality Assessment with Transformers, [Paper], [Code]
- (arXiv 2021.08) No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency, [Paper], [Code]
- (arXiv 2021.08) MUSIQ: Multi-scale Image Quality Transformer, [Paper], [Code]
- (arXiv 2021.10) VTAMIQ: Transformers for Attention Modulated Image Quality Assessment, [Paper]
- (arXiv 2021.12) Learning Transformer Features for Image Quality Assessment, [Paper]
- (arXiv 2022.03) Visual Mechanisms Inspired Efficient Transformers for Image and Video Quality Assessment, [Paper]
- (arXiv 2022.04) Multi-Scale Features and Parallel Transformers Based Image Quality Assessment, [Paper], [Code]
- (arXiv 2022.05) SwinIQA: Learned Swin Distance for Compressed Image Quality Assessment, [Paper]
- (arXiv 2022.05) MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion, [Paper]
- (arXiv 2022.08) DAHiTrA: Damage Assessment Using a Novel Hierarchical Transformer Architecture, [Paper]
- (arXiv 2022.10) DCVQE: A Hierarchical Transformer for Video Quality Assessment, [Paper]
- (arXiv 2023.03) ST360IQ: No-Reference Omnidirectional Image Quality Assessment with Spherical Vision Transformers, [Paper], [Code]
- (arXiv 2023.03) MRET: Multi-resolution Transformer for Video Quality Assessment, [Paper]
- (arXiv 2023.05) Blind Image Quality Assessment via Transformer Predicted Error Map and Perceptual Quality Token, [Paper], [Code]
- (arXiv 2023.08) Local Distortion Aware Efficient Transformer Adaptation for Image Quality Assessment, [Paper]
- (arXiv 2022.10) TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers, [Paper], [Code]
- (arXiv 2022.12) SMMix: Self-Motivated Image Mixing for Vision Transformers, [Paper], [Code]
- (arXiv 2023.05) Transformer-based Sequence Labeling for Audio Classification based on MFCCs, [Paper]
- (arXiv 2022.11) ASiT: Audio Spectrogram vIsion Transformer for General Audio Representation, [Paper]
- (arXiv 2023.03) Multiscale Audio Spectrogram Transformer for Efficient Audio Classification, [Paper]
- (arXiv 2023.03) ModEFormer: Modality-Preserving Embedding for Audio-Video Synchronization using Transformers, [Paper]
- (arXiv 2023.07) AVSegFormer: Audio-Visual Segmentation with Transformer, [Paper], [Code]
- (arXiv 2022.03) BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers, [Paper], [Code]
- (arXiv 2022.05) ViT-BEVSeg: A Hierarchical Transformer Network for Monocular Birds-Eye-View Segmentation, [Paper], [Code]
- (arXiv 2022.06) PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images, [Paper]
- (arXiv 2022.06) Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer, [Paper], [Code]
- (arXiv 2022.06) PolarFormer: Multi-camera 3D Object Detection with Polar Transformer, [Paper], [Code]
- (arXiv 2022.07) CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers, [Paper]
- (arXiv 2022.07) UniFormer: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird's-Eye-View, [Paper]
- (arXiv 2022.09) A Dual-Cycled Cross-View Transformer Network for Unified Road Layout Estimation and 3D Object Detection in the Bird's-Eye-View, [Paper]
- (arXiv 2022.09) BEV-LGKD: A Unified LiDAR-Guided Knowledge Distillation Framework for BEV 3D Object Detection, [Paper]
- (arXiv 2023.02) DA-BEV: Depth Aware BEV Transformer for 3D Object Detection, [Paper]
- (arXiv 2023.03) TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving, [Paper], [Code]
- (arXiv 2023.04) VoxelFormer: Bird's-Eye-View Feature Generation based on Dual-view Attention for Multi-view 3D Object Detection, [Paper], [Code]
- (arXiv 2023.04) FedBEVT: Federated Learning Bird's Eye View Perception Transformer in Road Traffic Systems, [Paper]
- (arXiv 2023.04) A Cross-Scale Hierarchical Transformer with Correspondence-Augmented Attention for inferring Bird's-Eye-View Semantic Segmentation, [Paper]
- (arXiv 2023.06) OCBEV: Object-Centric BEV Transformer for Multi-View 3D Object Detection, [Paper]
- (arXiv 2023.06) An Efficient Transformer for Simultaneous Learning of BEV and Lane Representations in 3D Lane Detection, [Paper]
- (arXiv 2023.07) HeightFormer: Explicit Height Modeling without Extra Data for Camera-only 3D Object Detection in Bird’s Eye View, [Paper]
- (arXiv 2023.08) UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation, [Paper], [Code]
- (arXiv 2021.01) CPTR: Full Transformer Network for Image Captioning, [Paper]
- (arXiv 2021.01) Dual-Level Collaborative Transformer for Image Captioning, [Paper]
- (arXiv.2021.02) VisualGPT: Data-efficient Image Captioning by Balancing Visual Input and Linguistic Knowledge from Pretraining, [Paper], [Code]
- (arXiv 2021.06) Semi-Autoregressive Transformer for Image Captioning, [Paper], [Code]
- (arXiv 2021.08) Optimizing Latency for Online Video Captioning Using Audio-Visual Transformers, [Paper]
- (arXiv 2021.08) Dual Graph Convolutional Networks with Transformer and Curriculum Learning for Image Captioning, [Paper], [Code]
- (arXiv 2021.09) Bornon: Bengali Image Captioning with Transformer-based Deep learning approach, [Paper]
- (arXiv 2021.09) Label-Attention Transformer with Geometrically Coherent Objects for Image Captioning, [Paper], [Code]
- (arXiv 2021.09) Geometry-Entangled Visual Semantic Transformer for Image Captioning, [Paper]
- (arXiv 2021.10) Geometry Attention Transformer with Position-aware LSTMs for Image Captioning, [Paper]
- (arXiv 2021.10) Bangla Image Caption Generation through CNN-Transformer based Encoder-Decoder Network, [Paper]
- (arXiv 2021.11) SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning, [Paper]
- (arXiv 2021.12) Injecting Semantic Concepts into End-to-End Image Captioning, [Paper]
- (arXiv 2022.01) Compact Bidirectional Transformer for Image Captioning, [Paper], [Code]
- (arXiv 2022.02) ACORT: A Compact Object Relation Transformer for Parameter Efficient Image Captioning, [Paper], [Code]
- (arXiv 2022.02) Deep soccer captioning with transformer: dataset, semantics-related losses, and multi-level evaluation, [Paper], [Code]
- (arXiv 2022.03) X-Trans2Cap: Cross-Modal Knowledge Transfer using Transformer for 3D Dense Captioning, [Paper]
- (arXiv 2022.03) End-to-End Transformer Based Model for Image Captioning, [Paper]
- (arXiv 2022.03) Quantifying Societal Bias Amplification in Image Captioning, [Paper]
- (arXiv 2022.04) Image Captioning In the Transformer Age, [Paper]
- (arXiv 2022.05) Dual-Level Decoupled Transformer for Video Captioning, [Paper]
- (arXiv 2022.05) Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning, [Paper], [Code]
- (arXiv 2022.06) Transformer-Based Multi-modal Proposal and Re-Rank for Wikipedia Image-Caption Matching, [Paper], [Code]
- (arXiv 2022.07) ExpansionNet: exploring the sequence length bottleneck in the Transformer for Image Captioning, [Paper], [Code]
- (arXiv 2022.07) GRIT: Faster and Better Image captioning Transformer Using Dual Visual Features, [Paper], [Code]
- (arXiv 2022.07) Retrieval-Augmented Transformer for Image Captioning, [Paper]
- (arXiv 2022.09) vieCap4H-VLSP 2021: Vietnamese Image Captioning for Healthcare Domain using Swin Transformer and Attention-based LSTM, [Paper], [Code]
- (arXiv 2022.11) VieCap4H - VLSP 2021: ObjectAoA -- Enhancing performance of Object Relation Transformer with Attention on Attention for Vietnamese image captioning, [Paper]
- (arXiv 2022.11) VLTinT: Visual-Linguistic Transformer-in-Transformer for Coherent Video Paragraph Captioning, [Paper], [Code]
- (arXiv 2022.11) GRiT: A Generative Region-to-text Transformer for Object Understanding, [Paper], [Code]
- (arXiv 2023.01) End-to-End 3D Dense Captioning with Vote2Cap-DETR, [Paper], [Code]
- (arXiv 2023.02) ADAPT: Action-aware Driving Caption Transformer, [Paper], [Code]
- (arXiv 2023.02) DEVICE: DEpth and VIsual ConcEpts Aware Transformer for TextCaps, [Paper]
- (arXiv 2023.03) Neighborhood Contrastive Transformer for Change Captioning, [Paper], [Code]
- (arXiv 2023.03) Comparative study of Transformer and LSTM Network with attention mechanism on Image Captioning, [Paper]
- (arXiv 2023.03) Text with Knowledge Graph Augmented Transformer for Video Captioning, [Paper]
- (arXiv 2023.05) Transforming Visual Scene Graphs to Image Captions, [Paper]
- (arXiv 2023.07) Embedded Heterogeneous Attention Transformer for Cross-lingual Image Captioning, [Paper]
- (arXiv 2023.08) RegionBLIP: A Unified Multi-modal Pre-training Framework for Holistic and Regional Comprehension, [Paper], [Code]
- (arXiv 2023.08) Enhancing image captioning with depth information using a Transformer-based framework, [Paper]
- (ICLR'21) MODELING LONG-RANGE INTERACTIONS WITHOUT ATTENTION, [Paper], [Code]
- (CVPR'20) Feature Pyramid Transformer, [Paper], [Code]
- (ICLR'21) An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, [Paper], [Code]
- (arXiv 2020.06) Visual Transformers: Token-based Image Representation and Processing for Computer Vision, [Paper]
- (arXiv 2020.12) Training data-efficient image transformers & distillation through attention, [Paper], [Code]
- (arXiv 2021.01) Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, [Paper], [Code]
- (arXiv 2021.01) Bottleneck Transformers for Visual Recognition, [Paper] , [Code]
- (arXiv.2021.02) Conditional Positional Encodings for Vision Transformers, [Paper], [Code]
- (arXiv.2021.02) Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions, [Paper], [Code]
- (arXiv 2021.03) Transformer in Transformer, [Paper], [Code]
- (arXiv 2021.03) ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases, [Paper], [Code]
- (arXiv 2021.03) Scalable Visual Transformers with Hierarchical Pooling, [Paper]
- (arXiv 2021.03) Incorporating Convolution Designs into Visual Transformers, [Paper]
- (arXiv 2021.03) DeepViT: Towards Deeper Vision Transformer, [Paper], [Code]
- (arXiv 2021.03) Swin Transformer: Hierarchical Vision Transformer using Shifted Windows, [Paper], [Code]
- (arXiv 2021.03) Understanding Robustness of Transformers for Image Classification, [Paper]
- (arXiv 2021.03) Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding, [Paper]
- (arXiv 2021.03) CvT: Introducing Convolutions to Vision Transformers, [Paper], [Code]
- (arXiv 2021.03) Rethinking Spatial Dimensions of Vision Transformers, [Paper], [Code]
- (arXiv 2021.03) Going deeper with Image Transformers, [Paper]
- (arXiv 2021.04) LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference, [Paper]
- (arXiv 2021.04) On the Robustness of Vision Transformers to Adversarial Examples, [Paper]
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- (arXiv 2023.07) Discovering Spatio-Temporal Rationales for Video Question Answering, [[Paper]](https://arxiv.org/