activity
20172026
most citedLearning to Generalize: Meta-Learning for Domain Generalization

113 citations · 116 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

CrowdGaussian: Reconstructing High-Fidelity 3D Gaussians for Human Crowd from a Single Image

Yizheng Song, Yiyu Zhuang, Qipeng Xu +5

Single-view 3D human reconstruction has garnered significant attention in recent years. Despite numerous advancements, prior research has concentrated on reconstructing 3D models f…

cs.CV2026

SemVideo: Reconstructs What You Watch from Brain Activity via Hierarchical Semantic Guidance

Minghan Yang, Lan Yang, Ke Li +3

Reconstructing dynamic visual experiences from brain activity provides a compelling avenue for exploring the neural mechanisms of human visual perception. While recent progress in…

cs.CV2025★ 3 cited

Annotation-Free Human Sketch Quality Assessment

Lan Yang, Kaiyue Pang, Honggang Zhang +1

As lovely as bunnies are, your sketched version would probably not do them justice (Fig.~\ref{fig:intro}). This paper recognises this very problem and studies sketch quality assess…

cs.CV2018

Learning to Sketch with Shortcut Cycle Consistency

Jifei Song, Kaiyue Pang, Yi-Zhe Song +2

To see is to sketch -- free-hand sketching naturally builds ties between human and machine vision. In this paper, we present a novel approach for translating an object photo to a s…

cs.LG2017★ 113 cited

Learning to Generalize: Meta-Learning for Domain Generalization

Da Li, Yongxin Yang, Yi-Zhe Song +1

Domain shift refers to the well known problem that a model trained in one source domain performs poorly when applied to a target domain with different statistics. {Domain Generaliz…