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20232026
most citedRetrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook

6 citations · 20 across the 35 of their papers we have counts for

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33 papers · 1 filter

cs.CV2026

Reinforcing Egocentric Spatial Perception in Multimodal Large Language Models via Ego Scene Augmentation

Chi Kit Wong, Ye Pan, Yuanhuiyi Lyu +6

Egocentric Visual Question Answering (VQA) has attracted widespread attention as an important task for enabling Multimodal Large Language Models (MLLMs) to interact with the real w…

cs.CV2026

Perceptual Flow Network for Visually Grounded Reasoning

Yangfu Li, Yuning Gong, Hongjian Zhan +8

Despite the success of Large-Vision Language Models (LVLMs), general optimization objectives (e.g., standard MLE) fail to constrain visual trajectories, leading to language bias an…

cs.CV2026

TC-AE: Unlocking Token Capacity for Deep Compression Autoencoders

Teng Li, Ziyuan Huang, Cong Chen +5

We propose TC-AE, a ViT-based architecture for deep compression autoencoders. Existing methods commonly increase the channel number of latent representations to maintain reconstruc…

cs.CV2026

SAP: Segment Any 4K Panorama

Lutao Jiang, Zidong Cao, Weikai Chen +14

Promptable instance segmentation is widely adopted in embodied and AR systems, yet the performance of foundation models trained on perspective imagery often degrades on 360° panora…

cs.CV2026

StruVis: Enhancing Reasoning-based Text-to-Image Generation via Thinking with Structured Vision

Yuanhuiyi Lyu, Kaiyu Lei, Ziqiao Weng +7

Reasoning-based text-to-image (T2I) generation requires models to interpret complex prompts accurately. Existing reasoning frameworks can be broadly categorized into two types: (1)…

cs.CV2026

EgoIntent: A Pre-Outcome Micro-Step Benchmark for Understanding What, Why, and Next

Ye Pan, Chi Kit Wong, Yuanhuiyi Lyu +8

Egocentric video provides a natural modality for studying human behavior, but conventional visual understanding captures mainly observable scenes, objects, and actions rather than…

cs.CV2025

DualCamCtrl: Dual-Branch Diffusion Model for Geometry-Aware Camera-Controlled Video Generation

Hongfei Zhang, Kanghao Chen, Zixin Zhang +6

This paper presents DualCamCtrl, a novel end-to-end diffusion model for camera-controlled video generation. Recent works have advanced this field by representing camera poses as ra…

cs.CV2025

T-Rex-Omni: Integrating Negative Visual Prompt in Generic Object Detection

Jiazhou Zhou, Qing Jiang, Kanghao Chen +4

Object detection methods have evolved from closed-set to open-set paradigms over the years. Current open-set object detectors, however, remain constrained by their exclusive relian…

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

PhysToolBench: Benchmarking Physical Tool Understanding for MLLMs

Zixin Zhang, Kanghao Chen, Xingwang Lin +6

The ability to use, understand, and create tools is a hallmark of human intelligence, enabling sophisticated interaction with the physical world. For any general-purpose intelligen…

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…

cs.CV2025

DiMeR: Disentangled Mesh Reconstruction Model

Lutao Jiang, Jiantao Lin, Kanghao Chen +7

We propose DiMeR, a novel geometry-texture disentangled feed-forward model with 3D supervision for sparse-view mesh reconstruction. Existing methods confront two persistent obstacl…

cs.CV2025

Are Multimodal Large Language Models Ready for Omnidirectional Spatial Reasoning?

Zihao Dongfang, Xu Zheng, Ziqiao Weng +5

The 180x360 omnidirectional field of view captured by 360-degree cameras enables their use in a wide range of applications such as embodied AI and virtual reality. Although recent…

cs.CV2025

Reducing Unimodal Bias in Multi-Modal Semantic Segmentation with Multi-Scale Functional Entropy Regularization

Xu Zheng, Yuanhuiyi Lyu, Lutao Jiang +3

Fusing and balancing multi-modal inputs from novel sensors for dense prediction tasks, particularly semantic segmentation, is critically important yet remains a significant challen…

cs.CV2025★ 6 cited

Retrieval Augmented Generation and Understanding in Vision: A Survey and New Outlook

Xu Zheng, Ziqiao Weng, Yuanhuiyi Lyu +7

Retrieval-augmented generation (RAG) has emerged as a pivotal technique in artificial intelligence (AI), particularly in enhancing the capabilities of large language models (LLMs)…

cs.CV2025★ 1 cited

MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation

Chenfei Liao, Xu Zheng, Yuanhuiyi Lyu +5

Research has focused on Multi-Modal Semantic Segmentation (MMSS), where pixel-wise predictions are derived from multiple visual modalities captured by diverse sensors. Recently, th…

cs.CV2025★ 1 cited

OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation

Ding Zhong, Xu Zheng, Chenfei Liao +5

Segment Anything Model 2 (SAM2) has emerged as a strong base model in various pinhole imaging segmentation tasks. However, when applying it to domain, the significant f…

cs.CV2025

From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers

Jiacheng Liu, Chang Zou, Yuanhuiyi Lyu +2

Diffusion Transformers (DiT) have revolutionized high-fidelity image and video synthesis, yet their computational demands remain prohibitive for real-time applications. To solve th…

cs.CV2025★ 1 cited

RealRAG: Retrieval-augmented Realistic Image Generation via Self-reflective Contrastive Learning

Yuanhuiyi Lyu, Xu Zheng, Lutao Jiang +5

Recent text-to-image generative models, e.g., Stable Diffusion V3 and Flux, have achieved notable progress. However, these models are strongly restricted to their limited knowledge…

cs.CV2024

MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection

Xu Zheng, Yuanhuiyi Lyu, Lutao Jiang +3

In this paper, we address the challenging modality-agnostic semantic segmentation (MaSS), aiming at centering the value of every modality at every feature granularity. Training wit…

cs.CV2024

SAVEn-Vid: Synergistic Audio-Visual Integration for Enhanced Understanding in Long Video Context

Jungang Li, Sicheng Tao, Yibo Yan +6

Endeavors have been made to explore Large Language Models for video analysis (Video-LLMs), particularly in understanding and interpreting long videos. However, existing Video-LLMs…