41 citations · 52 across the 12 of their papers we have counts for
12 papers
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…
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…
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…
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…
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…
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…
xLSTM-UNet can be an Effective 2D & 3D Medical Image Segmentation Backbone with Vision-LSTM (ViL) better than its Mamba Counterpart
Tianrun Chen, Chaotao Ding, Lanyun Zhu +5
Convolutional Neural Networks (CNNs) and Vision Transformers (ViT) have been pivotal in biomedical image segmentation, yet their ability to manage long-range dependencies remains c…
RESMatch: Referring Expression Segmentation in a Semi-Supervised Manner
Ying Zang, Chenglong Fu, Runlong Cao +5
Referring expression segmentation (RES), a task that involves localizing specific instance-level objects based on free-form linguistic descriptions, has emerged as a crucial fronti…
Deep3DSketch+: Obtaining Customized 3D Model by Single Free-Hand Sketch through Deep Learning
Ying Zang, Chenglong Fu, Tianrun Chen +3
As 3D models become critical in today's manufacturing and product design, conventional 3D modeling approaches based on Computer-Aided Design (CAD) are labor-intensive, time-consumi…
Deep3DSketch+\+: High-Fidelity 3D Modeling from Single Free-hand Sketches
Ying Zang, Chaotao Ding, Tianrun Chen +2
The rise of AR/VR has led to an increased demand for 3D content. However, the traditional method of creating 3D content using Computer-Aided Design (CAD) is a labor-intensive and s…
Deep3DSketch+: Rapid 3D Modeling from Single Free-hand Sketches
Tianrun Chen, Chenglong Fu, Ying Zang +4
The rapid development of AR/VR brings tremendous demands for 3D content. While the widely-used Computer-Aided Design (CAD) method requires a time-consuming and labor-intensive mode…
SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More
Tianrun Chen, Lanyun Zhu, Chaotao Ding +6
The emergence of large models, also known as foundation models, has brought significant advancements to AI research. One such model is Segment Anything (SAM), which is designed for…