12 citations · 45 across the 14 of their papers we have counts for
7 papers · 1 filter
ShareGPT4V: Improving Large Multi-Modal Models with Better Captions
Lin Chen, Jinsong Li, Xiaoyi Dong +5
In the realm of large multi-modal models (LMMs), efficient modality alignment is crucial yet often constrained by the scarcity of high-quality image-text data. To address this bott…
OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation
Qidong Huang, Xiaoyi Dong, Pan Zhang +6
Hallucination, posed as a pervasive challenge of multi-modal large language models (MLLMs), has significantly impeded their real-world usage that demands precise judgment. Existing…
MLLM-DataEngine: An Iterative Refinement Approach for MLLM
Zhiyuan Zhao, Linke Ouyang, Bin Wang +5
Despite the great advance of Multimodal Large Language Models (MLLMs) in both instruction dataset building and benchmarking, the independence of training and evaluation makes curre…
VIGC: Visual Instruction Generation and Correction
Bin Wang, Fan Wu, Xiao Han +8
The integration of visual encoders and large language models (LLMs) has driven recent progress in multimodal large language models (MLLMs). However, the scarcity of high-quality in…
FreeDrag: Feature Dragging for Reliable Point-based Image Editing
Pengyang Ling, Lin Chen, Pan Zhang +3
To serve the intricate and varied demands of image editing, precise and flexible manipulation in image content is indispensable. Recently, Drag-based editing methods have gained im…
BUOL: A Bottom-Up Framework with Occupancy-aware Lifting for Panoptic 3D Scene Reconstruction From A Single Image
Tao Chu, Pan Zhang, Qiong Liu +1
Understanding and modeling the 3D scene from a single image is a practical problem. A recent advance proposes a panoptic 3D scene reconstruction task that performs both 3D reconstr…
V3Det: Vast Vocabulary Visual Detection Dataset
Jiaqi Wang, Pan Zhang, Tao Chu +6
Recent advances in detecting arbitrary objects in the real world are trained and evaluated on object detection datasets with a relatively restricted vocabulary. To facilitate the d…