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20232026
most citedRecent Advances in Multi-modal 3D Intelligence: A Comprehensive Survey and Evaluation

3 citations · 3 across the 7 of their papers we have counts for

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cs.CV2026

Language-Guided Token Compression with Reinforcement Learning in Large Vision-Language Models

Sihan Cao, Jianwei Zhang, Pengcheng Zheng +7

Large Vision-Language Models (LVLMs) incur substantial inference costs due to the processing of a vast number of visual tokens. Existing methods typically struggle to model progres…

cs.CV2025

Implicit Counterfactual Learning for Audio-Visual Segmentation

Mingfeng Zha, Tianyu Li, Guoqing Wang +4

Audio-visual segmentation (AVS) aims to segment objects in videos based on audio cues. Existing AVS methods are primarily designed to enhance interaction efficiency but pay limited…

cs.CV2025

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy

Yiting Yang, Hao Luo, Yuan Sun +7

A prevalent approach in Parameter-Efficient Fine-Tuning (PEFT) of pre-trained Vision Transformers (ViT) involves freezing the majority of the backbone parameters and solely learnin…

cs.CV2024

Region-aware Distribution Contrast: A Novel Approach to Multi-Task Partially Supervised Learning

Meixuan Li, Tianyu Li, Guoqing Wang +3

In this study, we address the intricate challenge of multi-task dense prediction, encompassing tasks such as semantic segmentation, depth estimation, and surface normal estimation,…

cs.CV2023★ 3 cited

Recent Advances in Multi-modal 3D Intelligence: A Comprehensive Survey and Evaluation

Yinjie Lei, Zixuan Wang, Feng Chen +3

Multi-modal 3D Intelligence has gained considerable attention due to its wide applications in autonomous driving and world simulation, etc. Compared to conventional single-modal 3D…