5 citations · 17 across the 32 of their papers we have counts for
12 papers · 1 filter
MERIT: Multi-domain Efficient RAW Image Translation
Wenjun Huang, Shenghao Fu, Yian Jin +10
RAW images captured by different camera sensors exhibit substantial domain shifts due to varying spectral responses, noise characteristics, and tone behaviors, complicating their d…
Fair Context Learning for Evidence-Balanced Test-Time Adaptation in Vision-Language Models
Sanggeon Yun, Ryozo Masukawa, SungHeon Jeong +3
Vision-Language Models (VLMs) such as CLIP enable strong zero-shot recognition but suffer substantial degradation under distribution shifts. Test-Time Adaptation (TTA) aims to impr…
Draft and Refine with Visual Experts
Sungheon Jeong, Ryozo Masukawa, Jihong Park +5
While recent Large Vision-Language Models (LVLMs) exhibit strong multimodal reasoning abilities, they often produce ungrounded or hallucinated responses because they rely too heavi…
LVLM_CSP: Accelerating Large Vision Language Models via Clustering, Scattering, and Pruning for Reasoning Segmentation
Hanning Chen, Yang Ni, Wenjun Huang +4
Large Vision Language Models (LVLMs) have been widely adopted to guide vision foundation models in performing reasoning segmentation tasks, achieving impressive performance. Howeve…
Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection?
Zhiling Chen, Hanning Chen, Mohsen Imani +1
In industrial settings, the accurate detection of anomalies is essential for maintaining product quality and ensuring operational safety. Traditional industrial anomaly detection (…
Tell Me What to Track: Infusing Robust Language Guidance for Enhanced Referring Multi-Object Tracking
Wenjun Huang, Yang Ni, Hanning Chen +4
Referring multi-object tracking (RMOT) is an emerging cross-modal task that aims to localize an arbitrary number of targets based on a language expression and continuously track th…
Expanding Event Modality Applications through a Robust CLIP-Based Encoder
Sungheon Jeong, Hanning Chen, Sanggeon Yun +4
This paper introduces a powerful encoder that transfers CLIP`s capabilities to event-based data, enhancing its utility and expanding its applicability across diverse domains. While…
VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation
Hanning Chen, Yang Ni, Wenjun Huang +6
Vision Transformers (ViTs) have emerged as the backbone of many segmentation models, consistently achieving state-of-the-art (SOTA) performance. However, their success comes at a s…
Recoverable Anonymization for Pose Estimation: A Privacy-Enhancing Approach
Wenjun Huang, Yang Ni, Arghavan Rezvani +5
Human pose estimation (HPE) is crucial for various applications. However, deploying HPE algorithms in surveillance contexts raises significant privacy concerns due to the potential…
Vision Language Model for Interpretable and Fine-grained Detection of Safety Compliance in Diverse Workplaces
Zhiling Chen, Hanning Chen, Mohsen Imani +2
Workplace accidents due to personal protective equipment (PPE) non-compliance raise serious safety concerns and lead to legal liabilities, financial penalties, and reputational dam…
EcoSense: Energy-Efficient Intelligent Sensing for In-Shore Ship Detection through Edge-Cloud Collaboration
Wenjun Huang, Hanning Chen, Yang Ni +5
Detecting marine objects inshore presents challenges owing to algorithmic intricacies and complexities in system deployment. We propose a difficulty-aware edge-cloud collaborative…
TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection
Hanning Chen, Wenjun Huang, Yang Ni +6
Task-oriented object detection aims to find objects suitable for accomplishing specific tasks. As a challenging task, it requires simultaneous visual data processing and reasoning…