3 Result(s)
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Chapter and Conference Paper
Learning Connectivity of Neural Networks from a Topological Perspective
Seeking effective neural networks is a critical and practical field in deep learning. Besides designing the depth, type of convolution, normalization, and nonlinearities, the topological connectivity of neural...
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Chapter and Conference Paper
MimicDet: Bridging the Gap Between One-Stage and Two-Stage Object Detection
Modern object detection methods can be divided into one-stage approaches and two-stage ones. One-stage detectors are more efficient owing to straightforward architectures, but the two-stage detectors still tak...
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Chapter and Conference Paper
POI: Multiple Object Tracking with High Performance Detection and Appearance Feature
Detection and learning based appearance feature play the central role in data association based multiple object tracking (MOT), but most recent MOT works usually ignore them and only focus on the hand-crafted ...
