2 citations · 2 across the 9 of their papers we have counts for
10 papers
DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection
Wenyang Liu, Tianyi Liu, Dongshuo Zhang +2
Few-shot anomaly detection (FSAD) has recently benefited from vision-language models such as CLIP, which enable anomaly de?tection by aligning visual features with text description…
Towards Bitstream-corrupted Harsh Visual Understanding: Through Bitstream Language Modeling as Robust Semantic Priors
Chaoran Huang, Fangcheng Li, Tianyi Liu +2
Bitstream-corrupted Harsh Visual Understanding (BcHVU) aims to understand harshly degraded videos originally decoded from a severely corrupted bitstream in real-world multimedia co…
Bitstream Action Recognition is Byte Modeling
Fangcheng Li, Chaoran Huang, Tianyi Liu +5
Conventional action recognition typically relies on successful pixel decoding of the bitstream. However, bitstream corruption during storage or transmission may cause severe visual…
PromptSR: Cascade Prompting for Lightweight Image Super-Resolution
Wenyang Liu, Chen Cai, Jianjun Gao +4
Although the lightweight Vision Transformer has significantly advanced image super-resolution (SR), it faces the inherent challenge of a limited receptive field due to the window-b…
From Semantics, Scene to Instance-awareness: Distilling Foundation Model for Grounded Open-vocabulary Situation Recognition
Chen Cai, Tianyi Liu, Jianjun Gao +5
Recent Multimodal Large Language Models (MLLMs) exhibit strong zero-shot abilities but struggle with complex Grounded Situation Recognition (GSR) and are resource-intensive for edg…
SSH-Net: A Self-Supervised and Hybrid Network for Noisy Image Watermark Removal
Wenyang Liu, Jianjun Gao, Kim-Hui Yap
Visible watermark removal is challenging due to its inherent complexities and the noise carried within images. Existing methods primarily rely on supervised learning approaches tha…
ByteNet: Rethinking Multimedia File Fragment Classification through Visual Perspectives
Wenyang Liu, Kejun Wu, Tianyi Liu +3
Multimedia file fragment classification (MFFC) aims to identify file fragment types, e.g., image/video, audio, and text without system metadata. It is of vital importance in multim…
CL-HOI: Cross-Level Human-Object Interaction Distillation from Vision Large Language Models
Jianjun Gao, Chen Cai, Ruoyu Wang +4
Human-object interaction (HOI) detection has seen advancements with Vision Language Models (VLMs), but these methods often depend on extensive manual annotations. Vision Large Lang…
Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting
Chen Cai, Zheng Wang, Jianjun Gao +4
In recent years, the rapid increase in online video content has underscored the limitations of static Video Question Answering (VideoQA) models trained on fixed datasets, as they s…
CM2-Net: Continual Cross-Modal Mapping Network for Driver Action Recognition
Ruoyu Wang, Chen Cai, Wenqian Wang +4
Driver action recognition has significantly advanced in enhancing driver-vehicle interactions and ensuring driving safety by integrating multiple modalities, such as infrared and d…