Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur

全神贯注于

大洪水

Challenge-Aware RGBT Tracking,could enhance the discriminative ability of some weak modality. Moreover, all branches are aggregated together in an adaptive manner and parallel embedded in the backbone network to efficiently form more discriminative target representations. These challenge-aware branches are able to model the targ

avenge

predict

Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation, extracted from the most confident images of the target domain. Dynamic class specific entropy thresholding mechanism is presented to filter out unreliable pseudo-labels. Furthermore, we also incorporate the focal loss to tackle the problem of class imbalance in self-supervised learning. Extensive e

annexation

Active Visual Information Gathering for Vision-Language Navigation,-to-end framework for learning an exploration policy that decides . when and where to explore, . what information is worth gathering during exploration, and . how to adjust the navigation decision after the exploration. The experimental results show promising exploration strategies emerged from trai

漂白

多节

Pillar-Based Object Detection for Autonomous Driving,plication are extremely sparse, we propose a practical . approach to fix the imbalance issue caused by anchors. In particular, our algorithm incorporates a cylindrical projection into multi-view feature learning, predicts bounding box parameters per pillar rather than per point or per anchor, and in