weizhao-11

weizhao-11's Stars

• rohitgandikota/sliders

  Concept Sliders for Precise Control of Diffusion Models

  Language:Jupyter Notebook94874

• THUDM/CogVideo

  text and image to video generation: CogVideoX (2024) and CogVideo (ICLR 2023)

  Language:Python7.8k731

• Kobaayyy/Awesome-CVPR2024-CVPR2021-CVPR2020-Low-Level-Vision

  A Collection of Papers and Codes for CVPR2024/CVPR2021/CVPR2020 Low Level Vision

  960116

• gesanqiu/SNPE_Tutorial

  A simple tutorial of SNPE.

  Language:C++14138

• sniklaus/pytorch-spynet

  a reimplementation of Optical Flow Estimation using a Spatial Pyramid Network in PyTorch

  Language:Python31147

• anuragranj/spynet

  Spatial Pyramid Network for Optical Flow

  Language:Lua23148

• cswry/OSEDiff

  Language:Python1509

• ckkelvinchan/BasicVSR_PlusPlus

  Official repository of "BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment"

  Language:Python58964

• KAIST-VICLab/FMA-Net

  [CVPR 2024 Oral] Official repository of FMA-Net

  Language:Python61143

• cswry/SeeSR

  [CVPR2024] SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution

  Language:Python39125

• PathologyFoundation/plip

  Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

  Language:Python26127

• aigc-apps/EasyAnimate

  📺 An End-to-End Solution for High-Resolution and Long Video Generation Based on Transformer Diffusion

  Language:Python1.2k92

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python54.5k5.6k

• csguoh/MambaIR

  [ECCV2024] An official pytorch implement of the paper "MambaIR: A simple baseline for image restoration with state-space model".

  Language:Python42236

• zsyOAOA/ResShift

  ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting (NeurIPS@2023 Spotlight, TPAMI@2024)

  Language:Python87448

• Janspiry/Image-Super-Resolution-via-Iterative-Refinement

  Unofficial implementation of Image Super-Resolution via Iterative Refinement by Pytorch

  Language:Python3.6k462

• apache/tvm

  Open deep learning compiler stack for cpu, gpu and specialized accelerators

  Language:Python11.7k3.4k

• I2-Multimedia-Lab/CDFormer

  Language:Python915

• cvlab-yonsei/PISR

  An official implementation of "Learning with Privileged Information for Efficient Image Super-Resolution" (ECCV2020) in PyTorch.

  Language:Python24330

• cslxju/SuperResolution_AGDN_CVPRW2024

  "Attention Guidance Distillation Network for Efficient Image Super-Resolution" in 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

  Language:Python3

• icandle/DDistill-SR

  DDistill-SR: Reparameterized Dynamic Distillation Network for Lightweight Image Super-Resolution (TMM 2023)

  Language:Python17

• code-implementation1/Code6

  Language:Python2

• huawei-noah/Efficient-Computing

  Efficient computing methods developed by Huawei Noah's Ark Lab

  Language:Jupyter Notebook1.2k208

• htqin/awesome-model-quantization

  A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.

  1.8k203

• KindXiaoming/pykan

  Kolmogorov Arnold Networks

  Language:Jupyter Notebook14.7k1.4k

• harpreetsahota204/awesome-cvpr-2024

  🤩 An AWESOME Curated List of Papers, Workshops, Datasets, and Challenges from CVPR 2024

  Language:Python1298

• AccumulateMore/CV

  ✔（已完结）最全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】

  Language:Jupyter Notebook5.7k757

• mli/paper-reading

  深度学习经典、新论文逐段精读

  26.5k2.4k

• WongKinYiu/yolov9

  Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information

  Language:Python8.9k1.4k

• CVHub520/X-AnyLabeling

  Effortless data labeling with AI support from Segment Anything and other awesome models.

  Language:Python3.8k442