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[ICLR 2023] Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"
OpenTAD is an open-source temporal action detection (TAD) toolbox based on PyTorch.
[CVPR 2024] Official implementation of "Beyond Image Super-Resolution for Image Recognition with Task-Driven Perceptual Loss"
[IEEE TIP] Vision Transformers for Single Image Dehazing
A Collection of Papers and Codes for CVPR2024/CVPR2021/CVPR2020 Low Level Vision
😘 让你“爱”上 GitHub，解决访问时图裂、加载慢的问题。（无需安装）
A quickstart and benchmark for pytorch distributed training.
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
浙大软院研究生毕业论文 Latex 模版（非官方）2021夏季
Implementation of Vision Mamba from the paper: "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" It's 2.8x faster than DeiT and saves 86.8% GPU memory wh…
A complete computer science study plan to become a software engineer.
A fast and simple method for multi-planes detection from point cloud
(ECCV 2022 Oral) TO-Scene: A Large-scale Dataset for Understanding 3D Tabletop Scenes
[CVPR 2024] Code release for TransNeXt model
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation (NeurIPS 2023 Spotlight)
[CVPR 2024] SceneWiz3D: Towards Text-guided 3D Scene Composition
Official implementation of 'Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields'
pytorch structural similarity (SSIM) loss
Repository of Vision Transformer with Deformable Attention (CVPR2022) and DAT++: Spatially Dynamic Vision Transformerwith Deformable Attention
一个计算机视觉、机器学习与深度学习相关的项目，看课程的笔记还有自己做的程序
traiNNer: Deep learning framework for image and video super-resolution, restoration and image-to-image translation, for training and testing.
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
official code of “OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding”
DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks.