activity
20142025
most citedImproving the Transferability of Adversarial Examples with Arbitrary Style Transfer

30 citations · 41 across the 9 of their papers we have counts for

collaborators

9 papers

eess.SP2025

A Block Term Decomposition Model Based Algorithm for Tensor Completion of Multidimensional Harmonic Signals

Lei Wang, Xiao-Feng Gong, Xi-Yuan Liu +2

We consider tensor data completion of an incomplete observation of multidimensional harmonic (MH) signals. Unlike existing tensor-based techniques for MH retrieval (MHR), which mos…

cs.CV2024

OCTrack: Benchmarking the Open-Corpus Multi-Object Tracking

Zekun Qian, Ruize Han, Wei Feng +3

We study a novel yet practical problem of open-corpus multi-object tracking (OCMOT), which extends the MOT into localizing, associating, and recognizing generic-category objects of…

cs.CL20241 cited

Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals

Lida Chen, Zujie Liang, Xintao Wang +7

Large language models (LLMs) have achieved great success, but their occasional content fabrication, or hallucination, limits their practical application. Hallucination arises becau…

cs.CV20243 cited

Improving Continuous Sign Language Recognition with Adapted Image Models

Lianyu Hu, Tongkai Shi, Liqing Gao +2

The increase of web-scale weakly labelled image-text pairs have greatly facilitated the development of large-scale vision-language models (e.g., CLIP), which have shown impressive…

cs.CV20241 cited

LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks

Jianlang Chen, Xuhong Ren, Qing Guo +5

Visual object tracking plays a critical role in visual-based autonomous systems, as it aims to estimate the position and size of the object of interest within a live video. Despite…

cs.CV2024

Dynamic Spatial-Temporal Aggregation for Skeleton-Aware Sign Language Recognition

Lianyu Hu, Liqing Gao, Zekang Liu +1

Skeleton-aware sign language recognition (SLR) has gained popularity due to its ability to remain unaffected by background information and its lower computational requirements. Cur…