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Arthur Wu's Projects

awesome-cs-books icon awesome-cs-books

经典编程书籍大全,涵盖:计算机系统与网络、系统架构、算法与数据结构、前端开发、后端开发、移动开发、数据库、测试、项目与团队、程序员职业修炼、求职面试等

co-slam icon co-slam

[CVPR'23] Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM

den icon den

This is an official implementation of "DEN: Disentangling and Exchanging Network for Depth Completion" in TensorFlow.

dvsr icon dvsr

DVSR ("Consistent Direct Time-of-Flight Video Depth Super-Resolution"), CVPR 2023

fairmot icon fairmot

A simple baseline for one-shot multi-object tracking

jekyll-embed-video icon jekyll-embed-video

Embed videos in Jekyll webpages without a plugin (Youtube, Vimeo, Twitch, Streamable, Mixer, Google Drive clips + more)

lr-gesrec icon lr-gesrec

Long-tailed and Real-time Hand Gesture Recognition in the Radio-Frequency Spectrum

midas icon midas

Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"

mobilecameratemplate icon mobilecameratemplate

A HTML5, JS, CSS Camera interface template. Feel free to use it in your next Computer Vision or AI project.

normal_guided_depth_candidates icon normal_guided_depth_candidates

We proposed a depth completion method refined by leveraging surface normal estimation of neighboring pixels. In terms of target pixel, we remain the local neighbors depth consistence by projecting the predicted depth and ground truth depth of the neighboring pixels back to the target pixel through the surface normal vector.

parking-space-inference icon parking-space-inference

This is an implementation of "SENSOR BASED ON-STREET PARKING SPACE STATUS INFERENCE UPON A SEMI-SUPERVISED AND MULTI-TASK LEARNING NETWORK" in TensorFlow for parking slots status inference

simplerecon icon simplerecon

[ECCV 2022] SimpleRecon: 3D Reconstruction Without 3D Convolutions

slowfast icon slowfast

PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

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