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Yang Di's starred repositories

SEINE

[ICLR 2024] SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction

Language:PythonApache-2.0861 24 28

LaVie

LaVie: High-Quality Video Generation with Cascaded Latent Diffusion Models

Language:PythonApache-2.0790 26 23

LIA

[ICLR 22] Latent Image Animator: Learning to Animate Images via Latent Space Navigation

Language:PythonNOASSERTION578 28 23

awesome-uncertainty-deeplearning

This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.

MIT459 290

2D-Motion-Retargeting

PyTorch implementation for our paper Learning Character-Agnostic Motion for Motion Retargeting in 2D, SIGGRAPH 2019

Language:PythonMIT433 19 34

transmomo.pytorch

This is the official PyTorch implementation of the CVPR 2020 paper "TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting".

Language:Python390 22 24

We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datasets demonstrate that UniPose, with a ResNet backbone and Waterfall module, is a robust and efficient architecture for pose estimation obtaining state-of- the-art results in single person pose detection for both sin- gle images and videos.

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MutualGuide

Localize to Classify and Classify to Localize: Mutual Guidance in Object Detection

Language:PythonMIT111 4 7

GCL

Implementation for CVPR2021 paper "Joint Generative and Contrastive Learning for Unsupervised Person Re-identification"

Language:PythonMIT46 6 17

ICE

Implementation for ICCV 2021 paper "ICE: Inter-instance Contrastive Encoding for Unsupervised Person Re-identification"

Language:PythonMIT45 2 20

UNIK

[BMVC 2021 Oral] Official implementation of our paper "A Unified Framework for Real-world Skeleton-based Action Recognition" on Toyota Smarthome/Penn Action/NTU-RGB+D/Posetics datasets

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