winycg

winycg's Stars

• WongKinYiu/yolov7

  Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

  Language:Jupyter Notebook13.3k1131.8k4.2k

• mlfoundations/open_clip

  An open source implementation of CLIP.

  Language:Python9.9k77477957

• eriklindernoren/PyTorch-YOLOv3

  Minimal PyTorch implementation of YOLOv3

  Language:Python7.3k1037052.6k

• facebookresearch/mae

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

  Language:Python7.2k561911.2k

• rom1504/img2dataset

  Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.

  Language:Python3.6k31255336

• mohuangrui/ucasthesis

  LaTeX Thesis Template for the University of Chinese Academy of Sciences

  Language:TeX3.4k68429926

• mseitzer/pytorch-fid

  Compute FID scores with PyTorch.

  Language:Python3.3k1586505

• microsoft/Cream

  This is a collection of our NAS and Vision Transformer work.

  Language:Python1.7k35156225

• zoubohao/DenoisingDiffusionProbabilityModel-ddpm-

  This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

  Language:Python1.5k443159

• zhoubolei/bolei_awesome_posters

  CVPR and NeurIPS poster examples and templates. May we have in-person poster session soon!

  1.4k100134

• JunweiLiang/awesome_lists

  Awesome Lists for Tenure-Track Assistant Professors and PhD students. (助理教授/博士生生存指南)

  Language:Python1.4k33179

• rosinality/denoising-diffusion-pytorch

  Implementation of Denoising Diffusion Probabilistic Models in PyTorch

  Language:Python36051443

• google-research-datasets/conceptual-12m

  Conceptual 12M is a dataset containing (image-URL, caption) pairs collected for vision-and-language pre-training.

  35713618

• charlesCXK/RGBD_Semantic_Segmentation_PyTorch

  [ECCV 2020] PyTorch Implementation of some RGBD Semantic Segmentation models.

  Language:Python29543143

• yuanli2333/CKA-Centered-Kernel-Alignment

  Reproduce CKA: Similarity of Neural Network Representations Revisited

  Language:Python2816533

• alinlab/L2T-ww

  Learning What and Where to Transfer (ICML 2019)

  Language:Python25171048

• Hramchenko/diffusion_distiller

  🚀 PyTorch Implementation of "Progressive Distillation for Fast Sampling of Diffusion Models(v-diffusion)"

  Language:Python2116727

• LightDXY/FT-CLIP

  CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet

  Language:Python203467

• wusize/CLIPSelf

  [ICLR2024 Spotlight] Code Release of CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction

  Language:Python1616309

• altndrr/vic

  Code implementation of our NeurIPS 2023 paper: Vocabulary-free Image Classification

  Language:Python100673

• kaiyuyue/mgd

  Matching Guided Distillation (ECCV 2020)

  Language:Python635613

• winycg/CLIP-KD

  [CVPR-2024] Official implementations of CLIP-KD: An Empirical Study of CLIP Model Distillation

  Language:Python635120

• Rorozhl/CA-MKD

  This is the implementation for the ICASSP-2022 paper (Confidence-Aware Multi-Teacher Knowledge Distillation).

  Language:Python51114

• HDETR/H-Deformable-DETR-mmdet

  [CVPR2023] This is an official mmdet implementation of paper "DETRs with Hybrid Matching".

  Language:Python47124

• GzyAftermath/CAT-KD

  CVPR 2023, Class Attention Transfer Based Knowledge Distillation

  Language:Python32273

• Hao840/manifold-distillation

  Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation. NeurIPS 2022.

  Language:Python26210

• whoami-xu/srun_ict_2022

  登录脚本

  Language:Python1212

• Shengcao-Cao/MTPD

  [ICML 2023] MTPD: Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation

  Language:Python8113

• romech/fact-ai

  Implementation for 'Interpretable Complex-Valued Neural Networks for Privacy Protection'

  Language:Jupyter Notebook33142

• blue-blue272/Awesome-CLIP

  Awesome list for research on CLIP (Contrastive Language-Image Pre-Training).

  1000