15 citations · 51 across the 16 of their papers we have counts for
12 papers · 1 filter
LLaVA-RadZ: Can Multimodal Large Language Models Effectively Tackle Zero-shot Radiology Recognition?
Bangyan Li, Wenxuan Huang, Zhenkun Gao +8
Recently, Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in visual understanding and reasoning across various vision-language tasks. However, w…
Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models
Wenxuan Huang, Bohan Jia, Zijie Zhai +7
DeepSeek-R1-Zero has successfully demonstrated the emergence of reasoning capabilities in LLMs purely through Reinforcement Learning (RL). Inspired by this breakthrough, we explore…
Dynamic-LLaVA: Efficient Multimodal Large Language Models via Dynamic Vision-language Context Sparsification
Wenxuan Huang, Zijie Zhai, Yunhang Shen +6
Multimodal Large Language Models (MLLMs) have achieved remarkable success in vision understanding, reasoning, and interaction. However, the inference computation and memory increas…
HUWSOD: Holistic Self-training for Unified Weakly Supervised Object Detection
Liujuan Cao, Jianghang Lin, Zebo Hong +4
Most WSOD methods rely on traditional object proposals to generate candidate regions and are confronted with unstable training, which easily gets stuck in a poor local optimum. In…
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Chaoyou Fu, Yuhan Dai, Yongdong Luo +18
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus rem…
Fusion-Mamba for Cross-modality Object Detection
Wenhao Dong, Haodong Zhu, Shaohui Lin +6
Cross-modality fusing complementary information from different modalities effectively improves object detection performance, making it more useful and robust for a wider range of a…
Class-Imbalanced Semi-Supervised Learning for Large-Scale Point Cloud Semantic Segmentation via Decoupling Optimization
Mengtian Li, Shaohui Lin, Zihan Wang +3
Semi-supervised learning (SSL), thanks to the significant reduction of data annotation costs, has been an active research topic for large-scale 3D scene understanding. However, the…
Rethinking Centered Kernel Alignment in Knowledge Distillation
Zikai Zhou, Yunhang Shen, Shitong Shao +2
Knowledge distillation has emerged as a highly effective method for bridging the representation discrepancy between large-scale models and lightweight models. Prevalent approaches…
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise
Chaoyou Fu, Renrui Zhang, Zihan Wang +15
The surge of interest towards Multi-modal Large Language Models (MLLMs), e.g., GPT-4V(ision) from OpenAI, has marked a significant trend in both academia and industry. They endow L…
Weakly Supervised Open-Vocabulary Object Detection
Jianghang Lin, Yunhang Shen, Bingquan Wang +3
Despite weakly supervised object detection (WSOD) being a promising step toward evading strong instance-level annotations, its capability is confined to closed-set categories withi…
Aligning and Prompting Everything All at Once for Universal Visual Perception
Yunhang Shen, Chaoyou Fu, Peixian Chen +6
Vision foundation models have been explored recently to build general-purpose vision systems. However, predominant paradigms, driven by casting instance-level tasks as an object-wo…
Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization
Peixian Chen, Kekai Sheng, Mengdan Zhang +5
Open-vocabulary object detection (OVD) aims to scale up vocabulary size to detect objects of novel categories beyond the training vocabulary. Recent work resorts to the rich knowle…