Kunchang Li's repositories

CT-Net

[ICLR2021] official implementation of CT-Net

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Nightcrawler

Top-2 Solution for CVPR UG2+ Track2

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CS231n-Notes

Notes and resources for CS231n

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CrossFormer

The official code for the paper: https://arxiv.org/pdf/2108.00154.pdf

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EditAnything

Edit anything in images powered by segment-anything, ControlNet, StableDiffusion, etc.

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Kinetics-TPS-evaluation

fork from xiadingZ/Kinetics-TPS-evaluation

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Awesome-Anything

General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX

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catalyst

Accelerated deep learning R&D

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ConvNeXt

Code release for ConvNeXt model

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CrossViT

Official implementation of CrossViT. https://arxiv.org/abs/2103.14899

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deit

Official DeiT repository

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grounded-segment-any-parts

Grounded Segment Anything: From Objects to Parts

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Grounded-Segment-Anything

Marrying Grounding DINO with Segment Anything & Stable Diffusion - Detect , Segment and Generate Anything with Text Inputs

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HRFormer

This is an official implementation of our NeurIPS 2021 paper "HRFormer: High-Resolution Transformer for Dense Prediction".

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mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

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MAE-pytorch

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

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mmaction2

OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

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mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

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PaddleViT

:robot: PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+

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sd-webui-segment-anything

Segment Anything for Stable Diffusion Webui

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SKNet-PyTorch

Nearly Perfect & Easily Understandable PyTorch Implementation of SKNet

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SlowFast

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

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Swin-Transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

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transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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unilm

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

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VideoMAE

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

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visual-chatgpt

Official repo for the paper: Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models

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