The goal of this paper is Human-object Interaction (HO-I) detection. HO-I detection aims to find interacting human-objects regions and classify their interaction from an image. Researchers obtain significant improvement in recent years by relying on …
Annotation burden has become one of the biggest barriers to semantic segmentation. Approaches based on click-level annotations have therefore attracted increasing attention due to their superior trade-off between supervision and annotation cost. In …
Object localisation, in the context of regular images, often depicts objects like people or cars. In these images, there is typically a relatively small number of objects per class, which usually is manageable to annotate. However, outside the …
Skeleton-based action recognition has been extensively studied, but it remains an unsolved problem because of the complex variations of skeleton joints in 3-D spatiotemporal space. To handle this issue, we propose a newly temporal-then-spatial …
Machine learning and artificial intelligence play an ever more crucial role in mitigating important societal problems, such as the prevalence of hate speech. We describe the Hateful Memes Challenge competition, held at NeurIPS 2020, focusing on …
Domain generalization is challenging due to the domain shift and the uncertainty caused by the inaccessibility of target domain data. In this pa- per, we address both challenges with a probabilis- tic framework based on variational Bayesian in- …