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1 | # Awesome-Video-Object-Detection
2 | [](https://github.com/sindresorhus/awesome)
3 |
4 | 🔥🔥🔥 This repository lists some awesome video object detection series projects.
5 |
6 | ## Contents
7 | - [Awesome-Video-Object-Detection](#awesome-anchor-free-object-detection)
8 | - [Summary](#summary)
9 | - [Awesome List](#awesome-list)
10 | - [Frameworks](#frameworks)
11 |
12 | - ## Summary
13 |
14 | - ### Awesome List
15 |
16 | - [zhanghengdev/awesome-video-object-detection](https://github.com/zhanghengdev/awesome-video-object-detection) 
: This is a list of awesome articles about object detection from video.
17 |
18 | - [junliang230/video_object_detection_paper](https://github.com/junliang230/video_object_detection_paper) 
: record some video object detection papers and dataset (视频目标检测论文整理).
19 |
20 |
21 | ## Frameworks
22 |
23 | - [NoScope](https://github.com/stanford-futuredata/noscope) 
: "Noscope: optimizing neural network queries over video at scale". (**[arXiv 2017](https://arxiv.org/abs/1703.02529)**)
24 |
25 | - [FGFA](https://github.com/msracver/Flow-Guided-Feature-Aggregation) 
: "Flow-Guided Feature Aggregation for Video Object Detection". (**[ICCV 2017](https://openaccess.thecvf.com/content_iccv_2017/html/Zhu_Flow-Guided_Feature_Aggregation_ICCV_2017_paper.html)**)
26 |
27 | - [STSN](https://github.com/lyj96/STSN) 
: "Object Detection in Video with Spatiotemporal Sampling Networks". (**[ECCV 2018](https://openaccess.thecvf.com/content_ECCV_2018/html/Gedas_Bertasius_Object_Detection_in_ECCV_2018_paper.html)**)
28 |
29 | - [MANet](https://github.com/wangshy31/MANet_for_Video_Object_Detection) 
: "Fully Motion-Aware Network for Video Object Detection". (**[ECCV 2018](https://openaccess.thecvf.com/content_ECCV_2018/html/Shiyao_Wang_Fully_Motion-Aware_Network_ECCV_2018_paper.html)**)
30 |
31 | - RDN: "Relation Distillation Networks for Video Object Detection". (**[ICCV 2019](https://openaccess.thecvf.com/content_ICCV_2019/html/Deng_Relation_Distillation_Networks_for_Video_Object_Detection_ICCV_2019_paper.html)**)
32 |
33 | - [MGA](https://github.com/lhaof/Motion-Guided-Attention) 
: "Motion Guided Attention for Video Salient Object Detection". (**[ICCV 2019](https://openaccess.thecvf.com/content_ICCV_2019/html/Li_Motion_Guided_Attention_for_Video_Salient_Object_Detection_ICCV_2019_paper.html)**)
34 |
35 | - [SELSA](https://github.com/happywu/Sequence-Level-Semantics-Aggregation) 
: "Sequence level semantics aggregation for video object detection". (**[ICCV 2019](https://openaccess.thecvf.com/content_ICCV_2019/html/Wu_Sequence_Level_Semantics_Aggregation_for_Video_Object_Detection_ICCV_2019_paper.html)**)
36 |
37 | - [LSTS](https://github.com/jiangzhengkai/LSTS) 
: "Learning Where to Focus for Efficient Video Object Detection". (**[ECCV 2020](https://link.springer.com/chapter/10.1007/978-3-030-58517-4_2)**)
38 |
39 | - [HVR-Net](https://github.com/youthHan/HVRNet) 
: "Mining Inter-Video Proposal Relations for Video Object Detection". (**[ECCV 2020](https://link.springer.com/chapter/10.1007/978-3-030-58589-1_26)**)
40 |
41 | - [MEGA](https://github.com/Scalsol/mega.pytorch) 
: "Memory enhanced global-local aggregation for video object detection". (**[CVPR 2020](https://openaccess.thecvf.com/content_CVPR_2020/html/Chen_Memory_Enhanced_Global-Local_Aggregation_for_Video_Object_Detection_CVPR_2020_paper.html)**)
42 |
43 | - [PyramidCSA](https://github.com/guyuchao/PyramidCSA) 
: "Pyramid constrained self-attention network for fast video salient object detection". (**[AAAI 2020](https://ojs.aaai.org/index.php/AAAI/article/view/6718)**)
44 |
45 | - [REPP](https://github.com/AlbertoSabater/Robust-and-efficient-post-processing-for-video-object-detection) 
: "Robust and efficient post-processing for video object detection". (**[IROS 2020](https://ieeexplore.ieee.org/abstract/document/9341600)**)
46 |
47 | - [FFAVOD](https://github.com/hu64/FFAVOD) 
: "FFAVOD: Feature fusion architecture for video object detection". (**[Pattern Recognition Letters, 2021](https://www.sciencedirect.com/science/article/abs/pii/S016786552100307X)**)
48 |
49 | - [STMTrack](https://github.com/fzh0917/STMTrack) 
: "STMTrack: Template-free Visual Tracking with Space-time Memory Networks". (**[CVPR 2021](https://openaccess.thecvf.com/content/CVPR2021/html/Fu_STMTrack_Template-Free_Visual_Tracking_With_Space-Time_Memory_Networks_CVPR_2021_paper.html)**)
50 |
51 | - [TraDeS](https://github.com/JialianW/TraDeS) 
: "Track to Detect and Segment: An Online Multi-Object Tracker". (**[CVPR 2021](https://openaccess.thecvf.com/content/CVPR2021/html/Wu_Track_To_Detect_and_Segment_An_Online_Multi-Object_Tracker_CVPR_2021_paper.html)**)
52 |
53 | - [TROIA](https://github.com/open-mmlab/mmtracking) 
: "Temporal ROI Align for Video Object Recognition". (**[AAAI 2021](https://www.aaai.org/AAAI21Papers/AAAI-3370.GongT.pdf)**)
54 |
55 | - MeGA-CDA: "MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection". (**[CVPR 2021](https://openaccess.thecvf.com/content/CVPR2021/html/VS_MeGA-CDA_Memory_Guided_Attention_for_Category-Aware_Unsupervised_Domain_Adaptive_Object_CVPR_2021_paper.html)**)
56 |
57 | - [SSTVOS](https://github.com/dukebw/SSTVOS) 
: "SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation". (**[CVPR 2021](https://openaccess.thecvf.com/content/CVPR2021/html/Duke_SSTVOS_Sparse_Spatiotemporal_Transformers_for_Video_Object_Segmentation_CVPR_2021_paper.html)**)
58 |
59 | - [TransVOD](https://github.com/SJTU-LuHe/TransVOD) 
: "End-to-End Video Object Detection with Spatial-Temporal Transformers". (**[ACM 2021](https://arxiv.org/pdf/2105.10920.pdf)**)
60 |
61 | - [qianyuzqy/TransVOD_Lite](https://github.com/qianyuzqy/TransVOD_Lite) 
: (TPAMI 2023) TransVOD:End-to-End Video Object Detection with Spatial-Temporal Transformers (implementations of TransVOD Lite).
62 |
63 | - [VidVRD](https://github.com/Dawn-LX/VidVRD-tracklets) 
: "Video Relation Detection via Tracklet based Visual Transformer". (**[ACM 2021](https://arxiv.org/pdf/2108.08669.pdf)**)
64 |
65 | - [DSFNet](https://github.com/ChaoXiao12/Moving-object-detection-DSFNet) 
: "DSFNet: Dynamic and Static Fusion Network for Moving Object Detection in Satellite Videos". (**[IEEE Geoscience and Remote Sensing Letters 2021](https://ieeexplore.ieee.org/abstract/document/9594855)**)
66 |
67 | - [MAMBA](https://github.com/Duckduckgod/MAMBA) 
: Self implementation of AAAI21 paper MAMBA for video object detection. "MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection". (**[AAAI 2021](https://www.aaai.org/AAAI21Papers/AAAI-9815.SunG.pdf)**)
68 |
69 | - [STFT](https://github.com/lingyunwu14/STFT) 
: "Multi-frame Collaboration for Effective Endoscopic Video Polyp Detection via Spatial-Temporal Feature Transformation". (**[MICCAI 2021](https://link.springer.com/chapter/10.1007/978-3-030-87240-3_29)**)
70 |
71 | - [TAdaConv](https://github.com/alibaba-mmai-research/TAdaConv) 
: "TAda! Temporally-Adaptive Convolutions for Video Understanding". (**[ICLR 2022](https://arxiv.org/abs/2110.06178)**)
72 |
73 | - [TCTrack](https://github.com/vision4robotics/TCTrack) 
: "TCTrack: Temporal Contexts for Aerial Tracking". (**[CVPR 2022](https://arxiv.org/abs/2203.01885)**)
74 |
75 | - [SLT-Net](https://github.com/XuelianCheng/SLT-Net) 
: "Implicit Motion Handling for Video Camouflaged Object Detection". (**[CVPR 2022](https://arxiv.org/abs/2203.07363)**)
76 |
77 | - [StreamYOLO](https://github.com/yancie-yjr/StreamYOLO) 
: "Real-time Object Detection for Streaming Perception". (**[CVPR 2022](https://arxiv.org/abs/2203.12338v1)**)
78 |
79 | - [suyukun666/UFO](https://github.com/suyukun666/UFO) 
: "A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection". (**[arXiv 2022](https://arxiv.org/abs/2203.04708)**)
80 |
81 | - QueryProp: "QueryProp: Object Query Propagation for High-Performance Video Object Detection". (**[AAAI 2022](https://www.aaai.org/AAAI22Papers/AAAI-471.HeF.pdf)**)
82 |
83 | - [YOLOV](https://github.com/YuHengsss/YOLOV) 
: "YOLOV: Making Still Image Object Detectors Great at Video Object Detection". (**[arXiv 2022](https://arxiv.org/abs/2208.09686)**)
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