R-FCN: Object Detection via Region-based Fully Convolutional Networks [Object Detection] (2)
Pelee: A Real-Time Object Detection System on Mobile Devices [Object Detection] (1)
Fast R-CNN [Object Detection] (1)
(PTAV) Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking [Object Tracking] (1)
(MemTrack) Learning Dynamic Memory Networks for Object Tracking [Object Tracking] (1)
Deep Feature Flow for Video Recognition [Object Detection] (2)
(FGFA) Flow-Guided Feature Aggregation for Video Object Detection [Object Detection] (2)
(YOLO) You Only Look Once: Unifed, Real-Time Object Detection [Object Detection] (3)
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model [Human Pose Estimation] (1)
Towards Accurate Multi-person Pose Estimation in the Wild [Human Pose Estimation] (1)
(MGNet) Online object tracking via motion-guided convolutional neural network [Object Tracking] (3)
Detect-and-Track: Efficient Pose Estimation in Videos [Human Pose Estimation] (1)
Impression Network for Video Object Detection [Object Detection] (1)
(FlowTrack) End-to-end Flow Correlation Tracking with Spatial-temporal Attention [Object Tracking] (1)
(EAST) Learning Policies for Adaptive Tracking with Deep Feature Cascades [Object Tracking] (1)
CREST: Convolutional Residual Learning for Visual Tracking [Object Tracking] (1)
UCT: Learning Unified Convolutional Networks for Real-Time Visual Tracking [Object Tracking] (1)
Seq-NMS for Video Object Detection [Object Detection] (1)
(RASNet) Learning Attentions: Residual Attentional Siamese Network for High Performance Online Visual Tracking [Object Tracking] (1)
(SA-Siam) A Twofold Siamese Network for Real-Time Object Tracking [Object Tracking] (1)
(siameseFC) Fully-Convolutional Siamese Networks for Object Tracking [Object Tracking] (1)
FlowNet: Learning Optical Flow with Convolutional Networks [Convolutional Neural Network] (2)
(GOTURN) Learning to Track at 100 FPS with Deep Regression Networks [Object Tracking] (1)
U-Net: Convolutional Networks for Biomedical Image Segmentation [Segmentation] (2)
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models [Optimization / Training] (1)
YOLOv3: An incremental Improvement [Object Detection] (2)
(ADNet) Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning [Object Tracking] (3)
Neural Architecture Search with Reinforcement Learning [Optimization / Training] (1)
FusionNet - A deep fully residual convolutional neural network for image segmentation in connectomics [Segmentation] (1)
(MDNet) Learning Multi-Domain Convolutional Neural Networks for Visual Tracking [Object Tracking] (1)