6 papers
Towards Uniformity and Alignment for Multimodal Representation Learning
Wenzhe Yin, Pan Zhou, Zehao Xiao +4
Multimodal representation learning aims to construct a shared embedding space in which heterogeneous modalities are semantically aligned. Despite strong empirical results, InfoNCE-…
Probabilistic Prototype Calibration of Vision-Language Models for Generalized Few-shot Semantic Segmentation
Jie Liu, Jiayi Shen, Pan Zhou +2
Generalized Few-Shot Semantic Segmentation (GFSS) aims to extend a segmentation model to novel classes with only a few annotated examples while maintaining performance on base clas…
Probabilistic Interactive 3D Segmentation with Hierarchical Neural Processes
Jie Liu, Pan Zhou, Zehao Xiao +4
Interactive 3D segmentation has emerged as a promising solution for generating accurate object masks in complex 3D scenes by incorporating user-provided clicks. However, two critic…
CaPo: Cooperative Plan Optimization for Efficient Embodied Multi-Agent Cooperation
Jie Liu, Pan Zhou, Yingjun Du +4
In this work, we address the cooperation problem among large language model (LLM) based embodied agents, where agents must cooperate to achieve a common goal. Previous methods ofte…
Domain Adaptation with Cauchy-Schwarz Divergence
Wenzhe Yin, Shujian Yu, Yicong Lin +3
Domain adaptation aims to use training data from one or multiple source domains to learn a hypothesis that can be generalized to a different, but related, target domain. As such, h…
Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation
Jie Liu, Wenzhe Yin, Haochen Wang +3
Few-shot point cloud segmentation seeks to generate per-point masks for previously unseen categories, using only a minimal set of annotated point clouds as reference. Existing prot…