Abstract: There are two mainstream approaches for object detection: top-down and bottom-up. The state-of-the-art approaches are mainly top-down methods. In this paper, we demonstrate that bottom-up ...

All common tracking datasets (GOT-10k, OTB, VOT, UAV, TColor, DTB, NfS, LaSOT and TrackingNet) are supported. Support VOT2019 (ST/LT/RGBD/RGBT) downloading. Fix the randomness in ImageNet-VID (issue ...

Abstract: Deep Convolutional Neural Networks have been adopted for salient object detection and achieved the state-of-the-art performance. Most of the previous works however focus on region accuracy ...

Introducing Avro to the projects brings three main benefits: Reduction of data size and storage cost Decrease of the communication time and the network traffic between microservices Increased security ...