69 citations · 84 across the 4 of their papers we have counts for
5 papers · 1 filter
Network Architecture Search for Domain Adaptation
Yichen Li, Xingchao Peng
Deep networks have been used to learn transferable representations for domain adaptation. Existing deep domain adaptation methods systematically employ popular hand-crafted network…
Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation
Xingchao Peng, Yichen Li, Kate Saenko
Conventional unsupervised domain adaptation (UDA) studies the knowledge transfer between a limited number of domains. This neglects the more practical scenario where data are distr…
Learning 3D Part Assembly from a Single Image
Yichen Li, Kaichun Mo, Lin Shao +2
Autonomous assembly is a crucial capability for robots in many applications. For this task, several problems such as obstacle avoidance, motion planning, and actuator control have…
Learning Domain Adaptive Features with Unlabeled Domain Bridges
Yichen Li, Xingchao Peng
Conventional cross-domain image-to-image translation or unsupervised domain adaptation methods assume that the source domain and target domain are closely related. This neglects a…
Revisiting Image-Language Networks for Open-ended Phrase Detection
Bryan A. Plummer, Kevin J. Shih, Yichen Li +4
Most existing work that grounds natural language phrases in images starts with the assumption that the phrase in question is relevant to the image. In this paper we address a more…