3 citations · 3 across the 6 of their papers we have counts for
6 papers
VC-Tooler: Learning Compositional and Adaptive Visual Tool Use
Yizheng Wu, Jiashen Hua, Bing Deng +1
Agentic multimodal reasoning extends passive image understanding by allowing VLMs to actively acquire and refine visual evidence through visual tool interactions. Effective visual…
Illuminating Visual Identity in Universal Multimodal Embeddings
Jiawei Cao, Junyi Feng, Jiashen Hua +5
Universal Multimodal Embeddings (UMEs) aim to unify various modalities and tasks into a shared representation space. In recent years, this field has witnessed substantial progress…
Through the Lens of Contrast: Self-Improving Visual Reasoning in VLMs
Zhiyu Pan, Yizheng Wu, Jiashen Hua +5
Reasoning has emerged as a key capability of large language models. In linguistic tasks, this capability can be enhanced by self-improving techniques that refine reasoning paths fo…
Enhancing Weakly Supervised Multimodal Video Anomaly Detection through Text Guidance
Shengyang Sun, Jiashen Hua, Junyi Feng +1
Weakly supervised multimodal video anomaly detection has gained significant attention, yet the potential of the text modality remains under-explored. Text provides explicit semanti…
Online Convolutional Re-parameterization
Mu Hu, Junyi Feng, Jiashen Hua +4
Structural re-parameterization has drawn increasing attention in various computer vision tasks. It aims at improving the performance of deep models without introducing any inferenc…
Learning to Generate Content-Aware Dynamic Detectors
Junyi Feng, Jiashen Hua, Baisheng Lai +3
Model efficiency is crucial for object detection. Mostprevious works rely on either hand-crafted design or auto-search methods to obtain a static architecture, regardless ofthe dif…