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Quanjun Yin

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Quanjun Yin — 5 papers
  • Quanjun Yin — 4 papers, h 14
  • Quanjun Yin — 4 papers
  • Quanjun Yin — 1 paper
  • Quanjun Yin — 1 paper
  • Quanjun Yin — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedMulti-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2026

CityCube: Benchmarking Cross-view Spatial Reasoning on Vision-Language Models in Urban Environments

Haotian Xu, Yue Hu, Zhengqiu Zhu +7

Cross-view spatial reasoning is essential for embodied AI, underpinning spatial understanding, mental simulation and planning in complex environments. Existing benchmarks primarily…

cs.CV2025

Towards Autonomous UAV Visual Object Search in City Space: Benchmark and Agentic Methodology

Yatai Ji, Zhengqiu Zhu, Yong Zhao +7

Aerial Visual Object Search (AVOS) tasks in urban environments require Unmanned Aerial Vehicles (UAVs) to autonomously search for and identify target objects using visual and textu…

cs.CV2025

SwimVG: Step-wise Multimodal Fusion and Adaption for Visual Grounding

Liangtao Shi, Ting Liu, Xiantao Hu +3

Visual grounding aims to ground an image region through natural language, which heavily relies on cross-modal alignment. Most existing methods transfer visual/linguistic knowledge…

cs.CV2024★ 1 cited

Multi-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model

Ting Liu, Liangtao Shi, Richang Hong +3

The vision tokens in multimodal large language models usually exhibit significant spatial and temporal redundancy and take up most of the input tokens, which harms their inference…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.