17 citations · 61 across the 14 of their papers we have counts for
14 papers
FreeBind: Free Lunch in Unified Multimodal Space via Knowledge Fusion
Zehan Wang, Ziang Zhang, Xize Cheng +8
Unified multi-model representation spaces are the foundation of multimodal understanding and generation. However, the billions of model parameters and catastrophic forgetting probl…
Multi-Modal Domain Adaptation Across Video Scenes for Temporal Video Grounding
Haifeng Huang, Yang Zhao, Zehan Wang +2
Temporal Video Grounding (TVG) aims to localize the temporal boundary of a specific segment in an untrimmed video based on a given language query. Since datasets in this domain are…
Chat-Scene: Bridging 3D Scene and Large Language Models with Object Identifiers
Haifeng Huang, Yilun Chen, Zehan Wang +8
Recent advancements in 3D Large Language Models (LLMs) have demonstrated promising capabilities for 3D scene understanding. However, previous methods exhibit deficiencies in genera…
Extending Multi-modal Contrastive Representations
Zehan Wang, Ziang Zhang, Luping Liu +4
Multi-modal contrastive representation (MCR) of more than three modalities is critical in multi-modal learning. Although recent methods showcase impressive achievements, the high d…
Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes
Zehan Wang, Haifeng Huang, Yang Zhao +2
3D scene understanding has gained significant attention due to its wide range of applications. However, existing methods for 3D scene understanding are limited to specific downstre…
3DRP-Net: 3D Relative Position-aware Network for 3D Visual Grounding
Zehan Wang, Haifeng Huang, Yang Zhao +5
3D visual grounding aims to localize the target object in a 3D point cloud by a free-form language description. Typically, the sentences describing the target object tend to provid…
Distilling Coarse-to-Fine Semantic Matching Knowledge for Weakly Supervised 3D Visual Grounding
Zehan Wang, Haifeng Huang, Yang Zhao +5
3D visual grounding involves finding a target object in a 3D scene that corresponds to a given sentence query. Although many approaches have been proposed and achieved impressive p…
BuboGPT: Enabling Visual Grounding in Multi-Modal LLMs
Yang Zhao, Zhijie Lin, Daquan Zhou +3
LLMs have demonstrated remarkable abilities at interacting with humans through language, especially with the usage of instruction-following data. Recent advancements in LLMs, such…
Connecting Multi-modal Contrastive Representations
Zehan Wang, Yang Zhao, Xize Cheng +8
Multi-modal Contrastive Representation learning aims to encode different modalities into a semantically aligned shared space. This paradigm shows remarkable generalization ability…
DATE: Domain Adaptive Product Seeker for E-commerce
Haoyuan Li, Hao Jiang, Tao Jin +5
Product Retrieval (PR) and Grounding (PG), aiming to seek image and object-level products respectively according to a textual query, have attracted great interest recently for bett…
Video-Guided Curriculum Learning for Spoken Video Grounding
Yan Xia, Zhou Zhao, Shangwei Ye +3
In this paper, we introduce a new task, spoken video grounding (SVG), which aims to localize the desired video fragments from spoken language descriptions. Compared with using text…
AntCritic: Argument Mining for Free-Form and Visually-Rich Financial Comments
Huadai Liu, Wenqiang Xu, Xuan Lin +3
Argument mining aims to detect all possible argumentative components and identify their relationships automatically. As a thriving task in natural language processing, there has be…
AntPivot: Livestream Highlight Detection via Hierarchical Attention Mechanism
Yang Zhao, Xuan Lin, Wenqiang Xu +3
In recent days, streaming technology has greatly promoted the development in the field of livestream. Due to the excessive length of livestream records, it's quite essential to ext…
Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences
Zhu Zhang, Zhou Zhao, Yang Zhao +3
In this paper, we consider a novel task, Spatio-Temporal Video Grounding for Multi-Form Sentences (STVG). Given an untrimmed video and a declarative/interrogative sentence depictin…