1 citations · 2 across the 23 of their papers we have counts for
13 papers · 2 filters
VFAD: Variational Semantic Prompting Meets Frequency-Adaptive Representation Learning for Zero-Shot Anomaly Detection
Peng Chen, Kaige Li, Wei Wang +5
Zero-shot anomaly detection (ZSAD) aims to detect and localize anomalies in unseen categories without access to target-specific training data. Although recent CLIP-based methods ha…
SphereVAD: Training-Free Video Anomaly Detection via Geodesic Inference on the Unit Hypersphere
Chao Huang, Pengfei Wei, Penfei Wei +6
Video anomaly detection (VAD) aims to automatically identify events that deviate from normal patterns in untrimmed surveillance videos. Existing methods universally depend on large…
Multimodal Backdoor Attack on VLMs for Autonomous Driving via Graffiti and Cross-Lingual Triggers
Jiancheng Wang, Lidan Liang, Yong Wang +4
Visual language model (VLM) is rapidly being integrated into safety-critical systems such as autonomous driving, making it an important attack surface for potential backdoor attack…
A Patch-based Cross-view Regularized Framework for Backdoor Defense in Multimodal Large Language Models
Tianmeng Fang, Yong Wang, Zetai Kong +4
Multimodal large language models have become an important infrastructure for unified processing of visual and linguistic tasks. However, such models are highly susceptible to backd…
LongCat-Next: Lexicalizing Modalities as Discrete Tokens
Meituan LongCat Team, Bin Xiao, Chao Wang +86
The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal syste…
Stepping VLMs onto the Court: Benchmarking Spatial Intelligence in Sports
Yuchen Yang, Yuqing Shao, Duxiu Huang +11
Sports have long attracted broad attention as they push the limits of human physical and cognitive capabilities. Amid growing interest in spatial intelligence for vision-language m…
MPA: Multimodal Prototype Augmentation for Few-Shot Learning
Liwen Wu, Wei Wang, Lei Zhao +5
Recently, few-shot learning (FSL) has become a popular task that aims to recognize new classes from only a few labeled examples and has been widely applied in fields such as natura…
DLEBench: Evaluating Small-scale Object Editing Ability for Instruction-based Image Editing Model
Shibo Hong, Boxian Ai, Jun Kuang +5
Significant progress has been made in the field of Instruction-based Image Editing Models (IIEMs). However, while these models demonstrate plausible adherence to instructions and s…
SPDA-SAM: A Self-prompted Depth-Aware Segment Anything Model for Instance Segmentation
Yihan Shang, Wei Wang, Chao Huang +1
Recently, Segment Anything Model (SAM) has demonstrated strong generalizability in various instance segmentation tasks. However, its performance is severely dependent on the qualit…
Beyond Visual Safety: Jailbreaking Multimodal Large Language Models for Harmful Image Generation via Semantic-Agnostic Inputs
Mingyu Yu, Lana Liu, Zhehao Zhao +2
The rapid advancement of Multimodal Large Language Models (MLLMs) has introduced complex security challenges, particularly at the intersection of textual and visual safety. While e…
Advancing Adaptive Multi-Stage Video Anomaly Reasoning: A Benchmark Dataset and Method
Chao Huang, Benfeng Wang, Wei Wang +5
Recent progress in reasoning capabilities of Multimodal Large Language Models(MLLMs) has highlighted their potential for performing complex video understanding tasks. However, in t…
SuperOcc: Toward Cohesive Temporal Modeling for Superquadric-based 3D Occupancy Prediction
Zichen Yu, Quanli Liu, Wei Wang +2
3D occupancy prediction plays a pivotal role in the realm of autonomous driving, as it provides a comprehensive understanding of the driving environment. Most existing methods cons…
GeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models
Zhankai Ye, Bofan Li, Yukai Jin +5
Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-language reasoning. However, exis…