activity
20182023
most citedAdversarial Style Mining for One-Shot Unsupervised Domain Adaptation

66 citations · 168 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2023★ 2 cited

Entangled View-Epipolar Information Aggregation for Generalizable Neural Radiance Fields

Zhiyuan Min, Yawei Luo, Wei Yang +2

Generalizable NeRF can directly synthesize novel views across new scenes, eliminating the need for scene-specific retraining in vanilla NeRF. A critical enabling factor in these ap…

cs.CV2021★ 2 cited

Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes

Jian-Wei Zhang, Lei Lv, Yawei Luo +3

Few-shot segmentation~(FSS) performance has been extensively promoted by introducing episodic training and class-wise prototypes. However, the FSS problem remains challenging due t…

cs.CV2021★ 2 cited

VidFace: A Full-Transformer Solver for Video FaceHallucination with Unaligned Tiny Snapshots

Yuan Gan, Yawei Luo, Xin Yu +2

In this paper, we investigate the task of hallucinating an authentic high-resolution (HR) human face from multiple low-resolution (LR) video snapshots. We propose a pure transforme…

cs.CV2021

Improving Weakly-supervised Object Localization via Causal Intervention

Feifei Shao, Yawei Luo, Li Zhang +4

The recent emerged weakly supervised object localization (WSOL) methods can learn to localize an object in the image only using image-level labels. Previous works endeavor to perce…

cs.CV2021★ 20 cited

ClawCraneNet: Leveraging Object-level Relation for Text-based Video Segmentation

Chen Liang, Yu Wu, Yawei Luo +1

Text-based video segmentation is a challenging task that segments out the natural language referred objects in videos. It essentially requires semantic comprehension and fine-grain…

cs.CV2021★ 1 cited

Look, Cast and Mold: Learning 3D Shape Manifold from Single-view Synthetic Data

Qianyu Feng, Yawei Luo, Keyang Luo +1

Inferring the stereo structure of objects in the real world is a challenging yet practical task. To equip deep models with this ability usually requires abundant 3D supervision whi…