1 citations · 2 across the 6 of their papers we have counts for
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Rethinking Video-Text Understanding: Retrieval from Counterfactually Augmented Data
Wufei Ma, Kai Li, Zhongshi Jiang +5
Recent video-text foundation models have demonstrated strong performance on a wide variety of downstream video understanding tasks. Can these video-text models genuinely understand…
ImageNet3D: Towards General-Purpose Object-Level 3D Understanding
Wufei Ma, Guanning Zeng, Guofeng Zhang +5
A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D (e.g., class name and bounding box) and 3D information (e.g., 3D location a…
Uncertainty-Aware Deep Video Compression with Ensembles
Wufei Ma, Jiahao Li, Bin Li +1
Deep learning-based video compression is a challenging task, and many previous state-of-the-art learning-based video codecs use optical flows to exploit the temporal correlation be…
3D-Aware Visual Question Answering about Parts, Poses and Occlusions
Xingrui Wang, Wufei Ma, Zhuowan Li +2
Despite rapid progress in Visual question answering (VQA), existing datasets and models mainly focus on testing reasoning in 2D. However, it is important that VQA models also under…
Neural Textured Deformable Meshes for Robust Analysis-by-Synthesis
Angtian Wang, Wufei Ma, Alan Yuille +1
Human vision demonstrates higher robustness than current AI algorithms under out-of-distribution scenarios. It has been conjectured such robustness benefits from performing analysi…
Robust Category-Level 3D Pose Estimation from Synthetic Data
Jiahao Yang, Wufei Ma, Angtian Wang +3
Obtaining accurate 3D object poses is vital for numerous computer vision applications, such as 3D reconstruction and scene understanding. However, annotating real-world objects is…