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simplexsigil's Projects

4d-humans icon 4d-humans

4DHumans: Reconstructing and Tracking Humans with Transformers

afft icon afft

Code for the paper: Anticipative Feature Fusion Transformer for Multi-Modal Action Anticipation.

alphapose icon alphapose

Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

dpc icon dpc

Video Representation Learning by Dense Predictive Coding

e2fgvi icon e2fgvi

Official code for "Towards An End-to-End Framework for Flow-Guided Video Inpainting" (CVPR2022)

maskdino icon maskdino

[CVPR 2023] Official implementation of the paper "Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation"

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"

mmpose icon mmpose

OpenMMLab Pose Estimation Toolbox and Benchmark.

movinet-pytorch icon movinet-pytorch

MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;

openface icon openface

Face recognition with deep neural networks.

openpose icon openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

osx icon osx

Fork of OSX to adapt output writing.

p-hlvc icon p-hlvc

Implementation of Pose-based High Level View Contrasting for video representation learning

pyskl icon pyskl

A toolbox for skeleton-based action recognition.

pytorch-fcn icon pytorch-fcn

PyTorch Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)

skeleton-images icon skeleton-images

Code for skeleton image representations based on spatial structure of the skeleton joints (AVSS 2019 and SIBGRAPI 2019).

slowfast icon slowfast

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

ta3n icon ta3n

[ICCV 2019 (Oral)] Temporal Attentive Alignment for Large-Scale Video Domain Adaptation (PyTorch)

videomae icon videomae

VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

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