activity
20242026
collaborators

7 papers

cs.CV2026

Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation

Runlong Cao, Ying Zang, Chuanwei Zhou +4

Semi-supervised referring expression segmentation (SS-RES) aims to achieve precise pixel-level language grounding under limited annotation, yet suffers from limited supervision and…

cs.CV2025

SAM3-Adapter: Efficient Adaptation of Segment Anything 3 for Camouflage Object Segmentation, Shadow Detection, and Medical Image Segmentation

Tianrun Chen, Runlong Cao, Xinda Yu +8

The rapid rise of large-scale foundation models has reshaped the landscape of image segmentation, with models such as Segment Anything achieving unprecedented versatility across di…

cs.CV2025

Breaking the Box: Enhancing Remote Sensing Image Segmentation with Freehand Sketches

Ying Zang, Yuncan Gao, Jiangi Zhang +7

This work advances zero-shot interactive segmentation for remote sensing imagery through three key contributions. First, we propose a novel sketch-based prompting method, enabling…

cs.CV2025

Syllables to Scenes: Literary-Guided Free-Viewpoint 3D Scene Synthesis from Japanese Haiku

Chunan Yu, Yidong Han, Chaotao Ding +6

In the era of the metaverse, where immersive technologies redefine human experiences, translating abstract literary concepts into navigable 3D environments presents a fundamental c…

cs.CV2025

Let Human Sketches Help: Empowering Challenging Image Segmentation Task with Freehand Sketches

Ying Zang, Runlong Cao, Jianqi Zhang +8

Sketches, with their expressive potential, allow humans to convey the essence of an object through even a rough contour. For the first time, we harness this expressive potential to…

cs.CV2024

Magic3DSketch: Create Colorful 3D Models From Sketch-Based 3D Modeling Guided by Text and Language-Image Pre-Training

Ying Zang, Yidong Han, Chaotao Ding +2

The requirement for 3D content is growing as AR/VR application emerges. At the same time, 3D modelling is only available for skillful experts, because traditional methods like Comp…