2 citations · 3 across the 6 of their papers we have counts for
7 papers · 1 filter
Differences That Matter: Auditing Models for Capability Gap Discovery and Rectification
Qihao Liu, Chengzhi Mao, Yaojie Liu +2
Conventional evaluation methods for multimodal LLMs (MLLMs) lack interpretability and are often insufficient to fully disclose significant capability gaps across models. To address…
TriDiff-4D: Fast 4D Generation through Diffusion-based Triplane Re-posing
Eddie Pokming Sheung, Qihao Liu, Wufei Ma +3
With the increasing demand for 3D animation, generating high-fidelity, controllable 4D avatars from textual descriptions remains a significant challenge. Despite notable efforts in…
4D-Animal: Freely Reconstructing Animatable 3D Animals from Videos
Shanshan Zhong, Jiawei Peng, Zehan Zheng +6
Existing methods for reconstructing animatable 3D animals from videos typically rely on sparse semantic keypoints to fit parametric models. However, obtaining such keypoints is lab…
SpatialReasoner: Towards Explicit and Generalizable 3D Spatial Reasoning
Wufei Ma, Yu-Cheng Chou, Qihao Liu +4
Despite recent advances on multi-modal models, 3D spatial reasoning remains a challenging task for state-of-the-art open-source and proprietary models. Recent studies explore data-…
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…
Continual Adversarial Defense
Qian Wang, Hefei Ling, Yingwei Li +3
In response to the rapidly evolving nature of adversarial attacks against visual classifiers, numerous defenses have been proposed to generalize against as many known attacks as po…