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video detection papers based deep learning

• Towards High Performance for Mobiles: Xizhou Zhu, Jifeng Dai, Xingchi Zhu, Yichen Wei, Lu Yuan. "Towards High Performance Video Object Detection for Mobiles" Arxiv(2018). [ paper]

• Fully Motion-Aware Network: Shiyao Wang, Yucong Zhou, Junjie Yan, Zhidong Deng. "Fully Motion-Aware Network for Video Object Detection." ECCV (2018). [ code]

• SpatioTemporal Sampling Network: Gedas Bertasius, Lorenzo Torresani, ianbo Shi. "Object Detection in Video with Spatiotemporal Sampling Networks." ECCV (2018). [ paper]

• Aligned Spatial-Temporal Memory: Fanyi Xiao, Yong Jae Lee. "Video Object Detection with an Aligned Spatial-Temporal Memory." ECCV(2018). [ paper]

• Towards High Performance: Xizhou Zhu, Jifeng Dai, Lu Yuan, Yichen Wei. "Towards High Performance Video Object Detection." CVPR (2018). [ paper]
• Scale-Time Lattice: Kai Chen, Jiaqi Wang, Shuo Yang, Xingcheng Zhang, Yuanjun Xiong, Chen Chang Loy, Dahua Lin. "Optimizing Video Object Detection vis a Scale-Time Lattice." CVPR (2018). [ paper] [project]

• FGFA: Xizhou Zhu, Yujie Wang, Jifeng Dai, Lu Yuan, Yichen Wei. "Flow-Guided Feature Aggregation for Video Object Detection." ICCV (2017). [ paper]. [code]
• D_T: Christoph Feichtenhofer, Axel Pinz, Andrew Zisserman. "Detect to Track and Track to Detect." ICCV (2017). [ paper]. [project]

• DFF: Xizhou Zhu, Yuwen Xiong, Jifeng Dai, Lu Yuan, Yichen Wei. "Deep Feature Flow for Video Recognition." CVPR (2017). [paper] [code]

object detection papers based deep learning

• DetNet: Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun. "DetNet: A Backbone network for Object Detection." [paper]
• Light-Head R-CNN: Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun. "Light-Head R-CNN: In Defense of Two-Stage Object Detector."[paper]
• YOLOv3: Joseph Redmon, Ali Farhadi. "YOLOv3: An Incremental Improvement." [paper]

• IOU-Net: Borui Jiang, Ruixuan Luo, Jiayuan Mao, Tete Xiao, Yuning Jiang. "Acquisition of Localization Confidence for Accurate Object Detection." ECCV(2018). [ paper] [code]

• SNIP: Bharat Singh, Larry S. Davis. "An Analysis of Scale Invariance in Object Detection - SNIP." [paper] [code]
• Cascade-RCNN: Zhaowei Cai, Nuno Vasconcelos. "Cascade R-CNN: Delving into High Quality Object Detectio." [paper] [code]
• Relation-Networks: Han Hu, Jiayuan Gu, Zheng Zhang, Jifeng Dai, Yichen Wei. "Relation Networks for Object Detection." [paper] [code]

• YOLO9000: Joseph Redmon, Ali Farhadi. "YOLO9000: Better, Faster, Stronger." [paper] [project]

• R-FCN: Jifeng Dai, Yi Li, Kaiming He, Jian Sun. "R-FCN: Object Detection via Region-based Fully Convolutional Networks." [paper]

• YOLO: Joseph Redmon, Santosh Divvala, Ross Girshick, Ali Farhadi. "You Only Look Once: Unified, Real-Time Object Detection." [paper] [project]

• SSD: Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C.Berg. "SSD: Single Shot MultiBox Detector." [paper] [code]

• Faster R-CNN: Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun. "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks." [paper] [code]