[NeurIPS2022] Egocentric Video-Language Pretraining
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Updated
May 9, 2024 - Python
[NeurIPS2022] Egocentric Video-Language Pretraining
Official code and data for EgoBody dataset (2022 ECCV)
PyTorch code for EgoHMR (ICCV 2023): Probabilistic Human Mesh Recovery in 3D Scenes from Egocentric Views
[CVPR 2024] Official code for EgoGen: An Egocentric Synthetic Data Generator
Official implementation of Balanced Spherical Grid for Egocentric View Synthesis (CVPR 2023)
[CVPR 2022] Egocentric Action Target Prediction in 3D
[ICCV, 2023] Multiple humans in 3D captured by dynamic and static cameras in 4K.
Codebase for "Multimodal Distillation for Egocentric Action Recognition" (ICCV 2023)
EventEgo3D: 3D Human Motion Capture from Egocentric Event Streams [CVPR'24]
The champion solution for Ego4D Natural Language Queries Challenge in CVPR 2023
Code implementation for paper titled "HOI-Ref: Hand-Object Interaction Referral in Egocentric Vision"
✌️ Detection and tracking hand from FPV: benchmarks and challenges on rehabilitation exercises dataset
Official code repository to download the TREK-150 benchmark dataset and run experiments on it.
A dataset of egocentric vision, eye-tracking and full body kinematics from human locomotion in out-of-the-lab environments. Also, different use cases of the dataset along with example code.
The official PyTorch implementation of the IEEE/CVF Computer Vision and Pattern Recognition (CVPR) '24 paper PREGO: online mistake detection in PRocedural EGOcentric videos.
Official implementation of "A Backpack Full of Skills: Egocentric Video Understanding with Diverse Task Perspectives", accepted at CVPR 2024.
A collection of the forefront of Egocentric Human Activity Recognition (HAR) and Action Anticipation through Deep Learning
Official repository of the "Ego3DPose: Capturing 3D Cues from Binocular Egocentric Views" (SIGGRAPH Asia 2023)
Official repository of the "Attention-Propagation Network for Egocentric Heatmap to 3D Pose Lifting" (CVPR 2024 Highlight)
Deep Learning models to fuse imu-based motion capture and first-person video data to improve the prediction of future knee and ankle joint kinematics, in complex real-world environments.
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