Awesome-Computer-Vision

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Awesome-Computer-Vision

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Awesome Resources for Advanced Computer Vision Topics

Awesome-Computer-Vision 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# Awesome-Computer-Vision [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

## Highlighted Topics
*[1] Conditional Content Generation*: [awesome-conditional-content-generation](https://github.com/haofanwang/awesome-conditional-content-generation/)

## Hot Topics

*[1] Motion Prediction*: [awesome-3d-human-motion-prediction](https://github.com/aras62/vision-based-prediction/blob/master/papers/motion_papers.md)

*[2] 3D-Human-Reconstruction*: [awesome-3d-human-reconstruction](https://github.com/rlczddl/awesome-3d-human-reconstruction)

*[3] Virtual-Try-On*: [A Curated List of Awesome Virtual Try-on](https://github.com/minar09/awesome-virtual-try-on)

*[4] Talking Face*: [awesome_talking_face_generation](https://github.com/YunjinPark/awesome_talking_face_generation)

*[5] Sketch Generation*: [Awesome-Sketch-Synthesis](https://github.com/MarkMoHR/Awesome-Sketch-Synthesis)

*[6] Diffusion*: [Awesome-Diffusion-Models](https://github.com/heejkoo/Awesome-Diffusion-Models)

*[7] NeRF*: [awesome-NeRF](https://github.com/yenchenlin/awesome-NeRF)

*[8] CLIP*: [Awesome-CLIP](https://github.com/yzhuoning/Awesome-CLIP)

## Awesome Computer Vision

*[1] Graph Neural Network*: [GNN](https://github.com/thunlp/GNNPapers), [GNN](https://github.com/nnzhan/Awesome-Graph-Neural-Networks), [Graph Classification](https://github.com/benedekrozemberczki/awesome-graph-classification), [Adversarial GNN](https://github.com/safe-graph/graph-adversarial-learning-literature), [Deep GNN](https://github.com/mengliu1998/awesome-deep-gnn)

*[2] Video Analysis*: [Action Recognition](https://github.com/jinwchoi/awesome-action-recognition), [Temporal Action Detection](https://github.com/Rheelt/Materials-Temporal-Action-Detection), [Temporal Action Localization](https://github.com/Alvin-Zeng/Awesome-Temporal-Action-Localization)

*[3] Adversarial Attack*: [Adversarial Attack](https://nicholas.carlini.com/writing/2019/all-adversarial-example-papers.html), [Adversarial Learning]( https://github.com/nebula-beta/awesome-adversarial-deep-learning), [Robust ML](https://github.com/P2333/Papers-of-Robust-ML), [Graph Attack](https://github.com/ChandlerBang/awesome-graph-attack-papers)

*[4] 3D Vision*: [Point Cloud](https://github.com/Yochengliu/awesome-point-cloud-analysis), [3D Reconstruction](https://github.com/openMVG/awesome_3DReconstruction_list)

*[5] AutoML*: [AutoML](https://github.com/hibayesian/awesome-automl-papers), [Network Pruning](https://github.com/he-y/Awesome-Pruning), [Network Compression](https://github.com/sun254/awesome-model-compression-and-acceleration), [NAS](https://github.com/D-X-Y/Awesome-NAS)

*[6] Reinforcement Learning*: [RL](https://github.com/aikorea/awesome-rl), [RL](https://github.com/jgvictores/awesome-deep-reinforcement-learning), [Multiagent RL](https://github.com/chuangyc/awesome-multiagent-learning)

*[7] Transfer Learning*: [Transfer Learning](https://github.com/artix41/awesome-transfer-learning), [Zero Shot](https://github.com/chichilicious/awesome-zero-shot-learning), [Meta Learning](https://github.com/dragen1860/awesome-meta-learning)

*[8] GAN*: [GAN](https://github.com/nightrome/really-awesome-gan), [GAN Applications](https://github.com/nashory/gans-awesome-applications)

*[9] Object Detection*: [Detection](https://github.com/hoya012/deep_learning_object_detection), [Detection](https://github.com/amusi/awesome-object-detection)

*[10] Object Tracking*: [Multiple Object Tracking](https://github.com/SpyderXu/multi-object-tracking-paper-listn), [Tracking](https://github.com/foolwood/benchmark_results)

*[11] Pose Estimation*: [Human Pose Estimation](https://github.com/wangzheallen/awesome-human-pose-estimation), [Hand Pose Estimation](https://github.com/xinghaochen/awesome-hand-pose-estimation)

*[12] Segmentation*: [Semantic Segmentation](https://github.com/mrgloom/awesome-semantic-segmentation)

*[13] Classification*: [Image Classification](https://github.com/weiaicunzai/awesome-image-classification)

*[14] Vision-Language Navigation*: [Vision-Language Navigation](https://github.com/daqingliu/awesome-vln), [Self-Supervised Learning](https://github.com/jason718/awesome-self-supervised-learning)

*[15] Super Resolution*: [Super Resolution](https://github.com/ChaofWang/Awesome-Super-Resolution)

*[16] Denoising*: [Image Denoising](https://github.com/wenbihan/reproducible-image-denoising-state-of-the-art)

*[17] Anomaly Detection*: [Anomaly Detection](https://github.com/yzhao062/anomaly-detection-resources)

*[18] Interpretability*: [Interpretability](https://github.com/oneTaken/awesome_deep_learning_interpretability)

*[19] Trajectory Prediction*: [Trajectory-Prediction](https://github.com/xuehaouwa/Awesome-Trajectory-Prediction), [Interaction Aware Trajectory Prediction](https://github.com/jiachenli94/Awesome-Interaction-aware-Trajectory-Prediction)

*[20] OCR*: [image-text-localization-recognition](https://github.com/whitelok/image-text-localization-recognition/blob/master/README.zh-cn.md), [awesome-ocr](https://github.com/ChanChiChoi/awesome-ocr)

*[21] Transformer is all you need*: [Awesome Visual-Transformer](https://github.com/dk-liang/Awesome-Visual-Transformer), [BERT](https://github.com/tomohideshibata/BERT-related-papers), [Transformer-in-Vision](https://github.com/DirtyHarryLYL/Transformer-in-Vision)

*[22] MLP is all you need*: [awesome-mlp-papers](https://github.com/haofanwang/awesome-mlp-papers/)

*[23] Vision Language Pre-training*: [awesome-pretrained-chinese-nlp-models](https://github.com/lonePatient/awesome-pretrained-chinese-nlp-models), [awesome-vision-language-pretraining-papers](https://github.com/yuewang-cuhk/awesome-vision-language-pretraining-papers), [awesome-programming-language-pretraining-papers](https://github.com/yuewang-cuhk/awesome-programming-language-pretraining-papers), [PyContrast](https://github.com/HobbitLong/PyContrast), [contrastive_learning_codes](https://github.com/leerumor/contrastive_learning_codes)

*[24] Prompt*: [PromptPapers](https://github.com/thunlp/PromptPapers)

*[25] MIM*: [Masked Image Modeling](https://github.com/ucasligang/awesome-MIM)

*[21] Crowd Counting*: [Awesome-Crowd-Counting](https://github.com/gjy3035/Awesome-Crowd-Counting)

*[22] Video Analysis*: [Temporal Action Localization](https://github.com/Alvin-Zeng/Awesome-Temporal-Action-Localization), [Mulitple Object Tracking](https://github.com/luanshiyinyang/awesome-multiple-object-tracking), [Person ReID](https://github.com/bismex/Awesome-person-re-identification), [Video Person ReID](https://github.com/AsuradaYuci/awesome_video_person_reid)

*[23] Visual Reasoning*: [Visual Reasoning](https://github.com/jokieleung/awesome-visual-question-answering)

*[24] Visual Grounding*: [Visual Grounding](https://github.com/TheShadow29/awesome-grounding)

*[25] Video Inpainting*: [Awesome-Image-Inpainting](https://github.com/1900zyh/Awesome-Image-Inpainting)

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