2 citations · 5 across the 6 of their papers we have counts for
6 papers
Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning
Ruiqian Nai, Zixin Wen, Ji Li +2
In representation learning, a disentangled representation is highly desirable as it encodes generative factors of data in a separable and compact pattern. Researchers have advocate…
Orthogonal Annotation Benefits Barely-supervised Medical Image Segmentation
Heng Cai, Shumeng Li, Lei Qi +3
Recent trends in semi-supervised learning have significantly boosted the performance of 3D semi-supervised medical image segmentation. Compared with 2D images, 3D medical volumes i…
The Software Stack That Won the Formula Student Driverless Competition
Andres Alvarez, Nico Denner, Zhe Feng +13
This report describes our approach to design and evaluate a software stack for a race car capable of achieving competitive driving performance in the different disciplines of the F…
Planning for Sample Efficient Imitation Learning
Zhao-Heng Yin, Weirui Ye, Qifeng Chen +1
Imitation learning is a class of promising policy learning algorithms that is free from many practical issues with reinforcement learning, such as the reward design issue and the e…
Semantic-Aware Fine-Grained Correspondence
Yingdong Hu, Renhao Wang, Kaifeng Zhang +1
Establishing visual correspondence across images is a challenging and essential task. Recently, an influx of self-supervised methods have been proposed to better learn representati…
EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer
Chenyu Yang, Wanrong He, Yingqing Xu +1
Most existing methods view makeup transfer as transferring color distributions of different facial regions and ignore details such as eye shadows and blushes. Besides, they only ac…