Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/haofanwang/Awesome-Computer-Vision
Awesome Resources for Advanced Computer Vision Topics
https://github.com/haofanwang/Awesome-Computer-Vision
List: Awesome-Computer-Vision
3d-vision adversarial-attacks automl awesome-list computer-vision deep-learning denoising gan graph-neural-network interpretability object-detection paper pose-estimation super-resolution trajectory-prediction transfer-learning video-analysis vision-and-language vision-project
Last synced: 1 day ago
JSON representation
Awesome Resources for Advanced Computer Vision Topics
- Host: GitHub
- URL: https://github.com/haofanwang/Awesome-Computer-Vision
- Owner: haofanwang
- Created: 2019-07-31T06:08:51.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2023-01-05T16:29:12.000Z (almost 2 years ago)
- Last Synced: 2024-05-20T00:00:47.677Z (6 months ago)
- Topics: 3d-vision, adversarial-attacks, automl, awesome-list, computer-vision, deep-learning, denoising, gan, graph-neural-network, interpretability, object-detection, paper, pose-estimation, super-resolution, trajectory-prediction, transfer-learning, video-analysis, vision-and-language, vision-project
- Homepage:
- Size: 93.8 KB
- Stars: 210
- Watchers: 6
- Forks: 40
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-of-awesome-ml - Awesome-Computer-Vision (by haofanwang)
- awesome-mlp-papers - Awesome-Computer-Vision
- ultimate-awesome - Awesome-Computer-Vision - Awesome Resources for Advanced Computer Vision Topics. (Other Lists / PowerShell Lists)
README
# 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)