2 citations · 3 across the 19 of their papers we have counts for
20 papers
Boundary Voting Network for Ambiguity-Aware Timestamp-Supervised Action Segmentation
Runzhong Zhang, Yueqi Duan, Yang Chen +4
Timestamp-supervised action segmentation aims to segment and classify actions in untrimmed videos with a random frame annotated per action. Precisely localizing action boundaries f…
OneHOI: Unifying Human-Object Interaction Generation and Editing
Jiun Tian Hoe, Weipeng Hu, Xudong Jiang +2
Human-Object Interaction (HOI) modelling captures how humans act upon and relate to objects, typically expressed as <person, action, object> triplets. Existing approaches split int…
Spectral Defense Against Resource-Targeting Attack in 3D Gaussian Splatting
Yang Chen, Yi Yu, Jiaming He +3
Recent advances in 3D Gaussian Splatting (3DGS) deliver high-quality rendering, yet the Gaussian representation exposes a new attack surface, the resource-targeting attack. This at…
Boosting SAM for Cross-Domain Few-Shot Segmentation via Conditional Point Sparsification
Jiahao Nie, Yun Xing, Wenbin An +6
Motivated by the success of the Segment Anything Model (SAM) in promptable segmentation, recent studies leverage SAM to develop training-free solutions for few-shot segmentation, w…
E.M.Ground: A Temporal Grounding Vid-LLM with Holistic Event Perception and Matching
Jiahao Nie, Wenbin An, Gongjie Zhang +4
Despite recent advances in Video Large Language Models (Vid-LLMs), Temporal Video Grounding (TVG), which aims to precisely localize time segments corresponding to query events, rem…
CyIN: Cyclic Informative Latent Space for Bridging Complete and Incomplete Multimodal Learning
Ronghao Lin, Qiaolin He, Sijie Mai +5
Multimodal machine learning, mimicking the human brain's ability to integrate various modalities has seen rapid growth. Most previous multimodal models are trained on perfectly pai…
Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation
Jiahao Nie, Guanqiao Fu, Wenbin An +3
Cross-Domain Few-Shot Segmentation aims to segment categories in data-scarce domains conditioned on a few exemplars. Typical methods first establish few-shot capability in a large-…
MAP-VLA: Memory-Augmented Prompting for Vision-Language-Action Model in Robotic Manipulation
Runhao Li, Wenkai Guo, Zhenyu Wu +5
Pre-trained Vision-Language-Action (VLA) models have achieved remarkable success in improving robustness and generalization for end-to-end robotic manipulation. However, these mode…
E3RG: Building Explicit Emotion-driven Empathetic Response Generation System with Multimodal Large Language Model
Ronghao Lin, Shuai Shen, Weipeng Hu +5
Multimodal Empathetic Response Generation (MERG) is crucial for building emotionally intelligent human-computer interactions. Although large language models (LLMs) have improved te…
Towards Generalized Range-View LiDAR Segmentation in Adverse Weather
Longyu Yang, Lu Zhang, Jun Liu +4
LiDAR segmentation has emerged as an important task to enrich scene perception and understanding. Range-view-based methods have gained popularity due to their high computational ef…
MTL-UE: Learning to Learn Nothing for Multi-Task Learning
Yi Yu, Song Xia, Siyuan Yang +5
Most existing unlearnable strategies focus on preventing unauthorized users from training single-task learning (STL) models with personal data. Nevertheless, the paradigm has recen…
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Yi Yu, Song Xia, Xun Lin +5
Adversarial examples, characterized by imperceptible perturbations, pose significant threats to deep neural networks by misleading their predictions. A critical aspect of these exa…
Audio-Plane: Audio Factorization Plane Gaussian Splatting for Real-Time Talking Head Synthesis
Shuai Shen, Wanhua Li, Yunpeng Zhang +2
Talking head synthesis has emerged as a prominent research topic in computer graphics and multimedia, yet most existing methods often struggle to strike a balance between generatio…
Reference-free Human-Object Interaction Editing
Jiun Tian Hoe, Weipeng Hu, Wei Zhou +5
This paper presents InteractEdit, a novel framework for reference-free Human-Object Interaction (HOI) editing that tackles the challenging task of transforming an existing interact…
Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable Trigger
Yi Yu, Song Xia, Xun Lin +4
No-Reference Image Quality Assessment (NR-IQA), responsible for assessing the quality of a single input image without using any reference, plays a critical role in evaluating and o…
Unlearnable Examples Detection via Iterative Filtering
Yi Yu, Qichen Zheng, Siyuan Yang +6
Deep neural networks are proven to be vulnerable to data poisoning attacks. Recently, a specific type of data poisoning attack known as availability attacks has led to the failure…
MMRel: Benchmarking Relation Understanding in Multi-Modal Large Language Models
Jiahao Nie, Gongjie Zhang, Wenbin An +4
Though Multi-modal Large Language Models (MLLMs) have recently achieved significant progress, they often struggle to understand diverse and complicated inter-object relations. Spec…
Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders
Yi Yu, Yufei Wang, Song Xia +4
Unlearnable examples (UEs) seek to maximize testing error by making subtle modifications to training examples that are correctly labeled. Defenses against these poisoning attacks c…
Cross-Domain Few-Shot Segmentation via Iterative Support-Query Correspondence Mining
Jiahao Nie, Yun Xing, Gongjie Zhang +5
Cross-Domain Few-Shot Segmentation (CD-FSS) poses the challenge of segmenting novel categories from a distinct domain using only limited exemplars. In this paper, we undertake a co…
InteractDiffusion: Interaction Control in Text-to-Image Diffusion Models
Jiun Tian Hoe, Xudong Jiang, Chee Seng Chan +2
Large-scale text-to-image (T2I) diffusion models have showcased incredible capabilities in generating coherent images based on textual descriptions, enabling vast applications in c…