13 papers
CLIP-GS: Unifying Vision-Language Representation with 3D Gaussian Splatting
Siyu Jiao, Haoye Dong, Yuyang Yin +5
Recent works in 3D multimodal learning have made remarkable progress. However, typically 3D multimodal models are only capable of handling point clouds. Compared to the emerging 3D…
PreFM: Online Audio-Visual Event Parsing via Predictive Future Modeling
Xiao Yu, Yan Fang, Xiaojie Jin +2
Audio-visual event parsing plays a crucial role in understanding multimodal video content, but existing methods typically rely on offline processing of entire videos with huge mode…
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning
Shifang Zhao, Yiheng Lin, Lu Han +2
While anomaly detection has made significant progress, generating detailed analyses that incorporate industrial knowledge remains a challenge. To address this gap, we introduce Omn…
AlignGen: Boosting Personalized Image Generation with Cross-Modality Prior Alignment
Yiheng Lin, Shifang Zhao, Ting Liu +4
Personalized image generation aims to integrate user-provided concepts into text-to-image models, enabling the generation of customized content based on a given prompt. Recent zero…
3DResT: A Strong Baseline for Semi-Supervised 3D Referring Expression Segmentation
Wenxin Chen, Mengxue Qu, Weitai Kang +3
3D Referring Expression Segmentation (3D-RES) typically requires extensive instance-level annotations, which are time-consuming and costly. Semi-supervised learning (SSL) mitigates…
ROSE: Revolutionizing Open-Set Dense Segmentation with Patch-Wise Perceptual Large Multimodal Model
Kunyang Han, Yibo Hu, Mengxue Qu +3
Advances in CLIP and large multimodal models (LMMs) have enabled open-vocabulary and free-text segmentation, yet existing models still require predefined category prompts, limiting…