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MOTChallenge: A Benchmark for Single-camera Multiple Target Tracking
Standardized benchmarks have been crucial in pushing the performance of ...
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MOT20: A benchmark for multi object tracking in crowded scenes
Standardized benchmarks are crucial for the majority of computer vision ...
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Learn to Predict Sets Using Feed-Forward Neural Networks
This paper addresses the task of set prediction using deep feed-forward ...
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CVPR19 Tracking and Detection Challenge: How crowded can it get?
Standardized benchmarks are crucial for the majority of computer vision ...
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RGB-D Object Detection and Semantic Segmentation for Autonomous Manipulation in Clutter
Autonomous robotic manipulation in clutter is challenging. A large varie...
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PoseTrack: A Benchmark for Human Pose Estimation and Tracking
Human poses and motions are important cues for analysis of videos with p...
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Joint Learning of Set Cardinality and State Distribution
We present a novel approach for learning to predict sets using deep lear...
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Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking
Standardized benchmarks are crucial for the majority of computer vision ...
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DeepSetNet: Predicting Sets with Deep Neural Networks
This paper addresses the task of set prediction using deep learning. Thi...
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PoseTrack: Joint Multi-Person Pose Estimation and Tracking
In this work, we introduce the challenging problem of joint multi-person...
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RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Recently, very deep convolutional neural networks (CNNs) have shown outs...
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Online Multi-Target Tracking Using Recurrent Neural Networks
We present a novel approach to online multi-target tracking based on rec...
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MOT16: A Benchmark for Multi-Object Tracking
Standardized benchmarks are crucial for the majority of computer vision ...
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MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking
In the recent past, the computer vision community has developed centrali...
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Multiple Object Tracking: A Literature Review
Multiple Object Tracking (MOT) is an important computer vision problem w...
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