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cs.CV2025
Advancing 3D Scene Understanding with MV-ScanQA Multi-View Reasoning Evaluation and TripAlign Pre-training Dataset
Wentao Mo, Qingchao Chen, Yuxin Peng +2
The advancement of 3D vision-language (3D VL) learning is hindered by several limitations in existing 3D VL datasets: they rarely necessitate reasoning beyond a close range of obje…
cs.CV2024
3D Vision and Language Pretraining with Large-Scale Synthetic Data
Dejie Yang, Zhu Xu, Wentao Mo +3
3D Vision-Language Pre-training (3D-VLP) aims to provide a pre-train model which can bridge 3D scenes with natural language, which is an important technique for embodied intelligen…
cs.CV2024
Bridging the Gap between 2D and 3D Visual Question Answering: A Fusion Approach for 3D VQA
Wentao Mo, Yang Liu
In 3D Visual Question Answering (3D VQA), the scarcity of fully annotated data and limited visual content diversity hampers the generalization to novel scenes and 3D concepts (e.g.…