3 citations · 3 across the 9 of their papers we have counts for
4 papers · 1 filter
Tighnari v2: Mitigating Label Noise and Distribution Shift in Multimodal Plant Distribution Prediction via Mixture of Experts and Weakly Supervised Learning
Haixu Liu, Yufei Wang, Tianxiang Xu +2
Large-scale, cross-species plant distribution prediction plays a crucial role in biodiversity conservation, yet modeling efforts in this area still face significant challenges due…
Weak to Strong: VLM-Based Pseudo-Labeling as a Weakly Supervised Training Strategy in Multimodal Video-based Hidden Emotion Understanding Tasks
Yufei Wang, Haixu Liu, Tianxiang Xu +2
To tackle the automatic recognition of "concealed emotions" in videos, this paper proposes a multimodal weak-supervision framework and achieves state-of-the-art results on the iMiG…
Adaptive Disentangled Representation Learning for Incomplete Multi-View Multi-Label Classification
Quanjiang Li, Zhiming Liu, Tianxiang Xu +2
Multi-view multi-label learning frequently suffers from simultaneous feature absence and incomplete annotations, due to challenges in data acquisition and cost-intensive supervisio…
Adaptive Detector-Verifier Framework for Zero-Shot Polyp Detection in Open-World Settings
Shengkai Xu, Hsiang Lun Kao, Tianxiang Xu +9
Polyp detectors trained on clean datasets often underperform in real-world endoscopy, where illumination changes, motion blur, and occlusions degrade image quality. Existing approa…