activity
20202026
most citedLearning content and context with language bias for Visual Question Answering

3 citations · 6 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

BridgeAfford: Bridging Query-Target Gap for Generalizable 3D Affordance Grounding

Yijie Su, Yakun Zhu, Yi Bin +5

Language-guided 3D affordance grounding aims to localize functional regions on 3D objects according to interaction intents. However, existing methods exhibit poor generalization to…

cs.CV2026

VisualRouter: Query-Grounded Visual Sampling for Long Video Understanding

Haiyue Zhang, Yi Bin, Xun Jiang +5

Large vision-language models (LVLMs) have achieved significant progress in video understanding, yet understanding long videos remains challenging due to the large number of visual…

cs.CV2023

ScanERU: Interactive 3D Visual Grounding based on Embodied Reference Understanding

Ziyang Lu, Yunqiang Pei, Guoqing Wang +3

Aiming to link natural language descriptions to specific regions in a 3D scene represented as 3D point clouds, 3D visual grounding is a very fundamental task for human-robot intera…

cs.CV2020★ 3 cited

Learning content and context with language bias for Visual Question Answering

Chao Yang, Su Feng, Dongsheng Li +3

Visual Question Answering (VQA) is a challenging multimodal task to answer questions about an image. Many works concentrate on how to reduce language bias which makes models answer…

cs.CV2020★ 3 cited

PPGN: Phrase-Guided Proposal Generation Network For Referring Expression Comprehension

Chao Yang, Guoqing Wang, Dongsheng Li +3

Reference expression comprehension (REC) aims to find the location that the phrase refer to in a given image. Proposal generation and proposal representation are two effective tech…