ICCV 2021 We study the effectiveness of auxiliary self-supervised tasks to improve the out-of-distribution generalization of object detectors.
ICCV 2021 Oral We propose Warp Consistency, an unsupervised learning objective for dense correspondence regression.
ICCV 2021 Oral We propose a pixel-wise contrastive algorithm for semantic segmentation in the fully supervised setting.
ICCV 2021 Oral We propose a deep reparametrization of the maximum a posteriori formulation commonly employed in multi-frame image restoration tasks.
ICCV 2021 We demonstrated that an RL coach (Roach) would be a better choice to supervise imitation learning agents.
CVPR 2021 Oral We propose a simple yet effective multi-object tracking method in this paper.
ICRA 2021 A new visual model-based RL method with consideration of multiple hypotheses for future object movement.
arXiv 2021 We propose Attentive Feature Aggregation (AFA) to exploit both spatial and channel information for semantic segmentation and boundary detection.
CVPR 2020 Oral The largest driving video dataset for heterogeneous multitask learning.