MsterDC

MsterDC's Stars

• ncsu-dk-lab/Acc-DD

  Language:Python102

• Hansong-Zhang/M3D

  AAAI 2024, M3D: Dataset Condensation by Minimizing Maximum Mean Discrepancy

  Language:Python141

• rahulvigneswaran/Lottery-Ticket-Hypothesis-in-Pytorch

  This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adapted to any model/dataset.

  Language:Python31891

• snu-mllab/Efficient-Dataset-Condensation

  Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)

  Language:Python10213

• kaiwang960112/CAFE

  This is a method of dataset condensation, and it has been accepted by CVPR-2022.

  Language:Python604

• LINs-lab/RDED

  [CVPR 2024] On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm

  Language:Python451

• ICTMCG/Make-Your-Anchor

  [CVPR 2024] Make-Your-Anchor: A Diffusion-based 2D Avatar Generation Framework.

  Language:Python28316

• NUS-HPC-AI-Lab/DATM

  ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching

  Language:Python826

• OdysseusYuan/LKY_OfficeTools

  一键自动化 下载、安装、激活 Office 的利器。

  Language:C#8k730

• sdh0818/FreD

  Official PyTorch implementation for Frequency Domain-based Dataset Distillation [NeurIPS 2023]

  Language:Python251

• varun19299/rigl-reproducibility

  Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020

  Language:Python263

• verbose-void/rigl-torch

  Lightweight torch implementation of rigl, a sparse-to-sparse optimizer.

  Language:Jupyter Notebook536

• dvlab-research/ReviewKD

  Distilling Knowledge via Knowledge Review, CVPR 2021

  Language:Python24834

• dalinvip/Awesome-ChatGPT

  ChatGPT资料汇总学习，持续更新......

  4k384

• muzairkhattak/multimodal-prompt-learning

  [CVPR 2023] Official repository of paper titled "MaPLe: Multi-modal Prompt Learning".

  Language:Python57842

• GeorgeCazenavette/mtt-distillation

  Official code for our CVPR '22 paper "Dataset Distillation by Matching Training Trajectories"

  Language:Python37951

• VICO-UoE/DatasetCondensation

  Dataset Condensation (ICLR21 and ICML21)

  Language:Python45689

• tonyzhaozh/act

  Language:Python551139

• irfanICMLL/structure_knowledge_distillation

  The official code for the paper 'Structured Knowledge Distillation for Semantic Segmentation'. (CVPR 2019 ORAL) and extension to other tasks.

  Language:Python694104

• VILA-Lab/SRe2L

  (NeurIPS 2023 spotlight) Large-scale Dataset Distillation/Condensation, 50 IPC (Images Per Class) achieves the highest 60.8% on original ImageNet-1K val set.

  Language:Python10411

• Tramac/awesome-semantic-segmentation-pytorch

  Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

  Language:Python2.8k580

• mrgloom/awesome-semantic-segmentation

  :metal: awesome-semantic-segmentation

  10.4k2.5k

• chinhsuanwu/mobilevit-pytorch

  A PyTorch implementation of "MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer"

  Language:Python48266

• murufeng/awesome_lightweight_networks

  The implementation of various lightweight networks by using PyTorch. such as：MobileNetV2，MobileNeXt，GhostNet，ParNet，MobileViT、AdderNet，ShuffleNetV1-V2，LCNet，ConvNeXt，etc. ⭐⭐⭐⭐⭐

  Language:Python801155

• tonylins/pytorch-mobilenet-v2

  A PyTorch implementation of MobileNet V2 architecture and pretrained model.

  Language:Python1.4k329

• bigmb/Unet-Segmentation-Pytorch-Nest-of-Unets

  Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet

  Language:Python1.8k346

• milesial/Pytorch-UNet

  PyTorch implementation of the U-Net for image semantic segmentation with high quality images

  Language:Python8.7k2.4k

• facebookresearch/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

  Language:Python29.8k6.3k

• VainF/Torch-Pruning

  [CVPR 2023] Towards Any Structural Pruning; LLMs / SAM / Diffusion / Transformers / YOLOv8 / CNNs

  Language:Python2.5k310

• CVI-SZU/CCAM

  [CVPR 2022] C2AM: Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic Segmentation

  Language:Python18626