1 citations · 1 across the 5 of their papers we have counts for
6 papers
EVA01: Unified Native 3D Understanding and Generation via Mixture-of-Transformers
Zongyuan Yang, Mingjing Yi, Wanli Ma +8
This paper addresses the challenge of integrating 3D meshes as a native modality within Multimodal Large Language Models (MLLMs). Diffusion-based large reconstruction models decoup…
MR-Bench: Going Beyond Matching to Reasoning in Multimodal Retrieval
Junjie Zhou, Ze Liu, Lei Xiong +10
Multimodal retrieval is becoming a crucial component of modern AI applications, yet its evaluation lags behind the demands of more realistic and challenging scenarios. Existing ben…
MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval
Junjie Zhou, Zheng Liu, Ze Liu +6
Despite the rapidly growing demand for multimodal retrieval, progress in this field remains severely constrained by a lack of training data. In this paper, we introduce MegaPairs,…
DirectL: Efficient Radiance Fields Rendering for 3D Light Field Displays
Zongyuan Yang, Baolin Liu, Yingde Song +4
Autostereoscopic display, despite decades of development, has not achieved extensive application, primarily due to the daunting challenge of 3D content creation for non-specialists…
VISTA: Visualized Text Embedding For Universal Multi-Modal Retrieval
Junjie Zhou, Zheng Liu, Shitao Xiao +2
Multi-modal retrieval becomes increasingly popular in practice. However, the existing retrievers are mostly text-oriented, which lack the capability to process visual information.…
MLVU: Benchmarking Multi-task Long Video Understanding
Junjie Zhou, Yan Shu, Bo Zhao +9
The evaluation of Long Video Understanding (LVU) performance poses an important but challenging research problem. Despite previous efforts, the existing video understanding benchma…