What is your research area? My research topic, at a high level, hasn't changed much since my dissertation. It has always been the problem of physical scene understanding - building machines that see, reason about, and interact with the physical world. Besides learning algorithms, what are the levels of abstraction needed by Al systems in their representations, and where do they come from? I aim to answer these fundamental questions, drawing inspiration from nature, i.e., the physical world itself, and from human cognition.

With the built relation matrix and semantic-level representations, pixel representations can be augmented for pixel prediction.

Neural Information Processing Systems http://nips.cc/

Sequential recommendation aims to recommend the next item that matches a user's

To alleviate this issue, we propose Mask Matching Transformer (MM-Former), a new paradigm for the few-shot segmentation task.