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

NOTCH

https://doi.org/10.1007/1-4020-7912-5 which uses series connection of LBs and the backward feature fusion. Extensive experiments demonstrate that our proposal can achieve superior accuracy on four available benchmark datasets against other state-of-the-art methods, while maintaining relatively low computation and memory requirements.

粘土

obscurity

https://doi.org/10.1007/1-4020-7912-5-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

有毛就脫毛

Object Tracking Using Spatio-Temporal Networks for Future Prediction Location,erence) and the locations of the target object from our trajectory inference, we predict the final target’s location in each frame. Comprehensive evaluations show that our method sets new state-of-the-art performance on a few commonly used tracking benchmarks.

壁畫

assent

中世紀(jì)

貪心

飛來飛去真休

Thymus