activity
20192026
most citedOpen Set Domain Adaptation By Novel Class Discovery

8 citations · 10 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

IntriAdapt: Generalizable Intrinsic-Guided Test-Time Adaptation for Metric Geometry Estimation

Jiaxing Chen, Zizheng Yan, Jingyu Zhuang +4

Recovering metric 3D geometry from images is fundamentally ill-posed due to perspective projection ambiguity. Current geometry models incorporate supplied or predicted intrinsics d…

cs.CV2026

WildSplat: Feedforward Gaussian Splatting from Unposed In-the-Wild Images

Xiyu Zhang, Jingyu Zhuang, Hongjia Zhai +4

While feedforward 3D reconstruction excels at efficient novel view synthesis, it typically falters when faced with scenes under varying illumination. To this end, we introduce Wild…

cs.CV2026

LiveMoments: Reselected Key Photo Restoration in Live Photos via Reference-guided Diffusion

Clara Xue, Zizheng Yan, Zhenning Shi +5

Live Photo captures both a high-quality key photo and a short video clip to preserve the precious dynamics around the captured moment. While users may choose alternative frames as…

cs.CV2025

Ultra-High-Definition Reference-Based Landmark Image Super-Resolution with Generative Diffusion Prior

Zhenning Shi, Zizheng Yan, Yuhang Yu +6

Reference-based Image Super-Resolution (RefSR) aims to restore a low-resolution (LR) image by utilizing the semantic and texture information from an additional reference high-resol…

cs.CV2024

DAGSM: Disentangled Avatar Generation with GS-enhanced Mesh

Jingyu Zhuang, Di Kang, Linchao Bao +2

Text-driven avatar generation has gained significant attention owing to its convenience. However, existing methods typically model the human body with all garments as a single 3D m…

cs.CV2024

Credible Teacher for Semi-Supervised Object Detection in Open Scene

Jingyu Zhuang, Kuo Wang, Liang Lin +1

Semi-Supervised Object Detection (SSOD) has achieved resounding success by leveraging unlabeled data to improve detection performance. However, in Open Scene Semi-Supervised Object…

cs.CV2024★ 2 cited

TIP-Editor: An Accurate 3D Editor Following Both Text-Prompts And Image-Prompts

Jingyu Zhuang, Di Kang, Yan-Pei Cao +3

Text-driven 3D scene editing has gained significant attention owing to its convenience and user-friendliness. However, existing methods still lack accurate control of the specified…

cs.CV2023

DreamEditor: Text-Driven 3D Scene Editing with Neural Fields

Jingyu Zhuang, Chen Wang, Lingjie Liu +2

Neural fields have achieved impressive advancements in view synthesis and scene reconstruction. However, editing these neural fields remains challenging due to the implicit encodin…

cs.CV2022★ 8 cited

Open Set Domain Adaptation By Novel Class Discovery

Jingyu Zhuang, Ziliang Chen, Pengxu Wei +2

In Open Set Domain Adaptation (OSDA), large amounts of target samples are drawn from the implicit categories that never appear in the source domain. Due to the lack of their specif…

cs.LG2019

Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks

Ziliang Chen, Jingyu Zhuang, Xiaodan Liang +1

(Unsupervised) Domain Adaptation (DA) seeks for classifying target instances when solely provided with source labeled and target unlabeled examples for training. Learning domain-in…