45 citations · 164 across the 56 of their papers we have counts for
23 papers · 1 filter
EverybodyDance: Bipartite Graph-Based Identity Correspondence for Multi-Character Animation
Haotian Ling, Zequn Chen, Qiuying Chen +6
Consistent pose-driven character animation has achieved remarkable progress in single-character scenarios. However, extending these advances to multi-character settings is non-triv…
Towards Seamless Interaction: Causal Turn-Level Modeling of Interactive 3D Conversational Head Dynamics
Junjie Chen, Fei Wang, Zhihao Huang +5
Human conversation involves continuous exchanges of speech and nonverbal cues such as head nods, gaze shifts, and facial expressions that convey attention and emotion. Modeling the…
AffordBot: 3D Fine-grained Embodied Reasoning via Multimodal Large Language Models
Xinyi Wang, Xun Yang, Yanlong Xu +3
Effective human-agent collaboration in physical environments requires understanding not only what to act upon, but also where the actionable elements are and how to interact with t…
Dual Learning with Dynamic Knowledge Distillation and Soft Alignment for Partially Relevant Video Retrieval
Jianfeng Dong, Lei Huang, Daizong Liu +5
Almost all previous text-to-video retrieval works ideally assume that videos are pre-trimmed with short durations containing solely text-related content. However, in practice, vide…
Enhancing Partially Relevant Video Retrieval with Robust Alignment Learning
Long Zhang, Peipei Song, Jianfeng Dong +2
Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos partially relevant to a given query. The core challenge lies in learning robust query-video alignment ag…
MoCA: Identity-Preserving Text-to-Video Generation via Mixture of Cross Attention
Qi Xie, Yongjia Ma, Donglin Di +2
Achieving ID-preserving text-to-video (T2V) generation remains challenging despite recent advances in diffusion-based models. Existing approaches often fail to capture fine-grained…
Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning
Chongyuan Dai, Jinpeng Hu, Hongchang Shi +4
Amidst a shortage of qualified mental health professionals, the integration of large language models (LLMs) into psychological applications offers a promising way to alleviate the…
Video-EM: Event-Centric Episodic Memory for Long-Form Video Understanding
Yun Wang, Long Zhang, Jingren Liu +9
Video Large Language Models (Video-LLMs) have shown strong video understanding, yet their application to long-form videos remains constrained by limited context windows. A common w…
Audio Does Matter: Importance-Aware Multi-Granularity Fusion for Video Moment Retrieval
Junan Lin, Daizong Liu, Xianke Chen +5
Video Moment Retrieval (VMR) aims to retrieve a specific moment semantically related to the given query. To tackle this task, most existing VMR methods solely focus on the visual a…
Benchmarking and Bridging Emotion Conflicts for Multimodal Emotion Reasoning
Zhiyuan Han, Beier Zhu, Yanlong Xu +2
Despite their strong performance in multimodal emotion reasoning, existing Multimodal Large Language Models (MLLMs) often overlook the scenarios involving emotion conflicts, where…
QR-LoRA: Efficient and Disentangled Fine-tuning via QR Decomposition for Customized Generation
Jiahui Yang, Yongjia Ma, Donglin Di +6
Existing text-to-image models often rely on parameter fine-tuning techniques such as Low-Rank Adaptation (LoRA) to customize visual attributes. However, when combining multiple LoR…
MUPA: Towards Multi-Path Agentic Reasoning for Grounded Video Question Answering
Jisheng Dang, Huilin Song, Junbin Xiao +6
Grounded Video Question Answering (Grounded VideoQA) requires aligning textual answers with explicit visual evidence. However, modern multimodal models often rely on linguistic pri…
Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective
Ruixuan Zhang, He Wang, Zhengyu Zhao +4
Rapid advances in Artificial Intelligence Generated Images (AIGI) have facilitated malicious use, such as forgery and misinformation. Therefore, numerous methods have been proposed…
AlphaFuse: Learn ID Embeddings for Sequential Recommendation in Null Space of Language Embeddings
Guoqing Hu, An Zhang, Shuo Liu +3
Recent advancements in sequential recommendation have underscored the potential of Large Language Models (LLMs) for enhancing item embeddings. However, existing approaches face thr…
Structure-guided Diffusion Transformer for Low-Light Image Enhancement
Xiangchen Yin, Zhenda Yu, Longtao Jiang +4
While the diffusion transformer (DiT) has become a focal point of interest in recent years, its application in low-light image enhancement remains a blank area for exploration. Cur…
Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering
Peipei Song, Long Zhang, Long Lan +4
Partially relevant video retrieval (PRVR) is a practical yet challenging task in text-to-video retrieval, where videos are untrimmed and contain much background content. The pursui…
EgoTextVQA: Towards Egocentric Scene-Text Aware Video Question Answering
Sheng Zhou, Junbin Xiao, Qingyun Li +6
We introduce EgoTextVQA, a novel and rigorously constructed benchmark for egocentric QA assistance involving scene text. EgoTextVQA contains 1.5K ego-view videos and 7K scene-text…
A Survey on fMRI-based Brain Decoding for Reconstructing Multimodal Stimuli
Pengyu Liu, Guohua Dong, Dan Guo +5
In daily life, we encounter diverse external stimuli, such as images, sounds, and videos. As research in multimodal stimuli and neuroscience advances, fMRI-based brain decoding has…
CMMLoc: Advancing Text-to-PointCloud Localization with Cauchy-Mixture-Model Based Framework
Yanlong Xu, Haoxuan Qu, Jun Liu +2
The goal of point cloud localization based on linguistic description is to identify a 3D position using textual description in large urban environments, which has potential applica…
Precise Localization of Memories: A Fine-grained Neuron-level Knowledge Editing Technique for LLMs
Haowen Pan, Xiaozhi Wang, Yixin Cao +4
Knowledge editing aims to update outdated information in Large Language Models (LLMs). A representative line of study is locate-then-edit methods, which typically employ causal tra…
EgoBlind: Towards Egocentric Visual Assistance for the Blind
Junbin Xiao, Nanxin Huang, Hao Qiu +5
We present EgoBlind, the first egocentric VideoQA dataset collected from blind individuals to evaluate the assistive capabilities of contemporary multimodal large language models (…
AugRefer: Advancing 3D Visual Grounding via Cross-Modal Augmentation and Spatial Relation-based Referring
Xinyi Wang, Na Zhao, Zhiyuan Han +2
3D visual grounding (3DVG), which aims to correlate a natural language description with the target object within a 3D scene, is a significant yet challenging task. Despite recent a…
Tuning-Free Long Video Generation via Global-Local Collaborative Diffusion
Yongjia Ma, Junlin Chen, Donglin Di +6
Creating high-fidelity, coherent long videos is a sought-after aspiration. While recent video diffusion models have shown promising potential, they still grapple with spatiotempora…