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Found 5 papers, 1 papers with code
RT-MOT: Confidence-Aware Real-Time Scheduling Framework for Multi-Object Tracking Tasks
Focusing on multiple choices of a workload pair of detection and association, which are two main components of the tracking-by-detection approach for MOT, we tailor a measure of object confidence for RT-MOT and develop how to estimate the measure for the next frame of each MOT task.
SRF-GAN: Super-Resolved Feature GAN for Multi-Scale Representation
In this paper, we propose a novel generator for super-resolving features of the convolutional object detectors.
Object Detection based on Region Decomposition and Assembly
However, the detection accuracy is degraded often because of the low discriminability of object CNN features caused by occlusions and inaccurate region proposals.
Rank of Experts: Detection Network Ensemble
The recent advances of convolutional detectors show impressive performance improvement for large scale object detection.
Robust Online Multi-Object Tracking based on Tracklet Confidence and Online Discriminative Appearance Learning
We first propose the tracklet confidence using the detectability and continuity of a tracklet, and formulate a multi-object tracking problem based on the tracklet confidence.
