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20242026
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cs.CV2026

Inline Critic Steers Image Editing

Weitai Kang, Xiaohang Zhan, Yizhou Wang +4

Instruction-based image editing exhibits heterogeneous difficulty not only across cases but also across regions of an image, motivating refinement approaches that allocate correcti…

cs.CV2025

VGent: Visual Grounding via Modular Design for Disentangling Reasoning and Prediction

Weitai Kang, Jason Kuen, Mengwei Ren +3

Current visual grounding models are either based on a Multimodal Large Language Model (MLLM) that performs auto-regressive decoding, which is slow and risks hallucinations, or on r…

cs.CV2025

ExpVG: Investigating the Design Space of Visual Grounding in Multimodal Large Language Model

Weitai Kang, Weiming Zhuang, Zhizhong Li +2

Fine-grained multimodal capability in Multimodal Large Language Models (MLLMs) has emerged as a critical research direction, particularly for tackling the visual grounding (VG) pro…

cs.CV2025

3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation

Wenxin Chen, Mengxue Qu, Weitai Kang +3

3D Referring Expression Segmentation (3D-RES) typically requires extensive instance-level annotations, which are time-consuming and costly. Semi-supervised learning (SSL) mitigates…

cs.CV2025

Intent3D: 3D Object Detection in RGB-D Scans Based on Human Intention

Weitai Kang, Mengxue Qu, Jyoti Kini +3

In real-life scenarios, humans seek out objects in the 3D world to fulfill their daily needs or intentions. This inspires us to introduce 3D intention grounding, a new task in 3D o…

cs.CV2024

ACTRESS: Active Retraining for Semi-supervised Visual Grounding

Weitai Kang, Mengxue Qu, Yunchao Wei +1

Semi-Supervised Visual Grounding (SSVG) is a new challenge for its sparse labeled data with the need for multimodel understanding. A previous study, RefTeacher, makes the first att…