most citedRetrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook

6 citations · 7 across the 8 of their papers we have counts for

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cs.CV2026

Panoramic Affordance Prediction

Zixin Zhang, Chenfei Liao, Hongfei Zhang +10

Affordance prediction serves as a critical bridge between perception and action in embodied AI. However, existing research is confined to pinhole camera models, which suffer from n…

cs.CV2025

Multimodal Spatial Reasoning in the Large Model Era: A Survey and Benchmarks

Xu Zheng, Zihao Dongfang, Lutao Jiang +17

Humans possess spatial reasoning abilities that enable them to understand spaces through multimodal observations, such as vision and sound. Large multimodal reasoning models extend…

cs.CV2025

Don't Just Chase "Highlighted Tokens" in MLLMs: Revisiting Visual Holistic Context Retention

Xin Zou, Di Lu, Yizhou Wang +5

Despite their powerful capabilities, Multimodal Large Language Models (MLLMs) suffer from considerable computational overhead due to their reliance on massive visual tokens. Recent…

cs.CV2025

Are We Using the Right Benchmark: An Evaluation Framework for Visual Token Compression Methods

Chenfei Liao, Wensong Wang, Zichen Wen +10

Recent efforts to accelerate inference in Multimodal Large Language Models (MLLMs) have largely focused on visual token compression. The effectiveness of these methods is commonly…

cs.CV2025

Understanding-in-Generation: Reinforcing Generative Capability of Unified Model via Infusing Understanding into Generation

Yuanhuiyi Lyu, Chi Kit Wong, Chenfei Liao +5

Recent works have made notable advancements in enhancing unified models for text-to-image generation through the Chain-of-Thought (CoT). However, these reasoning methods separate t…

cs.CV2025

PANORAMA: The Rise of Omnidirectional Vision in the Embodied AI Era

Xu Zheng, Chenfei Liao, Ziqiao Weng +12

Omnidirectional vision, using 360-degree vision to understand the environment, has become increasingly critical across domains like robotics, industrial inspection, and environment…