activity
20202026
most citedFuzzy Positive Learning for Semi-supervised Semantic Segmentation

2 citations · 5 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2026

Tune-Your-Style: Intensity-tunable 3D Style Transfer with Gaussian Splatting

Yian Zhao, Rushi Ye, Ruochong Zheng +6

3D style transfer refers to the artistic stylization of 3D assets based on reference style images. Recently, 3DGS-based stylization methods have drawn considerable attention, prima…

cs.CV2025

iSegMan: Interactive Segment-and-Manipulate 3D Gaussians

Yian Zhao, Wanshi Xu, Ruochong Zheng +3

The efficient rendering and explicit nature of 3DGS promote the advancement of 3D scene manipulation. However, existing methods typically encounter challenges in controlling the ma…

cs.CV2024

GraCo: Granularity-Controllable Interactive Segmentation

Yian Zhao, Kehan Li, Zesen Cheng +6

Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity output and…

cs.CV2024

FaceChain-SuDe: Building Derived Class to Inherit Category Attributes for One-shot Subject-Driven Generation

Pengchong Qiao, Lei Shang, Chang Liu +3

Subject-driven generation has garnered significant interest recently due to its ability to personalize text-to-image generation. Typical works focus on learning the new subject's p…

cs.CV2023★ 1 cited

Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning

Yu Wang, Pengchong Qiao, Chang Liu +3

Recent advances in robust semi-supervised learning (SSL) typically filter out-of-distribution (OOD) information at the sample level. We argue that an overlooked problem of robust S…

cs.CV2022★ 2 cited

Fuzzy Positive Learning for Semi-supervised Semantic Segmentation

Pengchong Qiao, Zhidan Wei, Yu Wang +6

Semi-supervised learning (SSL) essentially pursues class boundary exploration with less dependence on human annotations. Although typical attempts focus on ameliorating the inevita…