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Video-Detection

video detection papers based deep learning

Arxiv

  • Looking Fast and Slow: Mason Liu, Menglong Zhu, Marie White, Yinxiao Li, Dmitry Kalenichenko. "Looking Fast and Slow: Memory-Guided Mobile Video Object Detection" Arxiv(2019). [ paper]
  • 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]

ECCV2020

  • LSTS: Zhengkai Jiang, Yu Liu, Ceyuan Yang, Jihao Liu, Peng Gao, Qian Zhang, Shiming Xiang, Chunhong Pan. "Learning Where to Focus for Efficient Video Object Detection" ECCV(2020). [ paper] [code]

CVPR2020

  • MEGA: Yihong Chen, Yue Cao, Han Hu, Liwei Wang. "Memory Enhanced Global-Local Aggregation for Video Object Detection" CVPR(2020). [ paper]

ICCV2019

  • Sequence Level Semantics Aggregation: Haiping Wu, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang. "Sequence Level Semantics Aggregation for Video Object Detection" ICCV(2019). [ paper]

  • Average Delay: Huizi Mao, Xiaodong Yang, William J. Dally. "A Delay Metric for Video Object Detection: What Average Precision Fails to Tell." ICCV (2019). [ paper]

  • Relation Distillation Networks: Jiajun Deng, Yingwei Pan, Ting Yao, Wengang Zhou, Houqiang Li, Tao Mei. "Relation Distillation Networks for Video Object Detection." ICCV (2019). [ paper]

AAAI2019

  • Locally-Weighted Deformable Neighbors: Zhengkai Jiang, Peng Gao, Chaoxu Guo, Qian Zhang, Shiming Xiang, Chunhong Pan. "Video Object Detection with Locally-Weighted Deformable Neighbors" AAAI(2019). [ paper]

ECCV2018

  • 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]

CVPR2018

  • 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]
  • Mobile Video Object Detection: Mason Liu, Menglong Zhu. "Mobile Video Object Detection with Temporally-Aware Feature Maps." CVPR (2018). [ paper]

ICCV2017

  • 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]

CVPR2017

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

Object-Detection

object detection papers based deep learning

Arxiv

  • 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]

ECCV2018

  • DetNet: Zeming Li, Chao Peng, Gang Yu, Xiangyu Zhang, Yangdong Deng, Jian Sun. "DetNet: A Backbone network for Object Detection." [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]

CVPR2018

  • 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]

ICCV2017

  • RetinaNet: Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, Piotr Dollar. "Focal Loss for Dense Object Detection." [paper]
  • Mask R-CNN: Kaiming He, Georgia Gkioxari, Piotr Dollar, Ross Girshick. "Mask R-CNN." [paper] [caffe2_code][pytorch_code]

CVPR2017

  • YOLO9000: Joseph Redmon, Ali Farhadi. "YOLO9000: Better, Faster, Stronger." [paper] [project]
  • FPN: Tsung-Yi Lin, Piotr Dollar, Ross Girshick, Kaiming He, Bharath Hariharan, Serge Belongie. "Feature Pyramid Networks for Object Detection." [paper]

NIPS2016

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

ECCV2016

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

CVPR2016

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

NIPS2015

  • 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]

ICCV2015

  • Fast R-CNN: Ross Girshick. "Fast R-CNN." [paper]

CVPR2014

  • R-CNN: Ross Girshick, Jeff Donahue, Trevor Darrell, Jitendra Malik. "Rich feature hierarchies for accurate object detection and semantic segmentation." [paper]