7 papers
2nd Place Solution to the HANDS 2026 Workshop Challenge-Dexterous Grasp Motion Track: Single-Shot Trajectory Warping for Grasp Motion Generation
Muneeb A. Khan, Woojin Kim, Shinwoo Kim +3
This report describes our 2nd place solution to the HANDS 2026 workshop challenge (Dexterous Grasp Motion track) in conjunction with ECCV 2026. In this challenge, we address grasp…
3rd Place Solution to Human Motion Challenges in Real-World and Clinical Settings (MoCha) @ECCV2026: Language-Aligned Motion Representations for Domain-Generalizable UPDRS-Gait Severity Estimation
Soojie Kim, Muhammad Munsif, Minkyung Kim +1
In this work, we introduce language-aligned motion representations for domain-generalizable UPDRS-Gait severity estimation, aiming to learn semantically structured motion features…
Privacy-Preserving Action Recognition: Taxonomy, Methods, and Privacy-Utility Trade-offs
Sareer Ul Amin, Muhammad Ayaz, Muhammad Munsif +1
Video surveillance in public safety, healthcare, and smart environments has made continuous human monitoring routine, raising real risks to personal identity and appearance. Privac…
DREAM: Extending Vision-Language Models with Dual-Objective Encoding for Cross-Modal Retrieval
Kaleem Ullah, Altaf Hussain, Muhammad Munsif +1
In today's media-driven world, the exponential growth of video content across domains such as surveillance, education, and entertainment has made retrieving semantically relevant v…
AVAR-Net: A Lightweight Audio-Visual Anomaly Recognition Framework with a Benchmark Dataset
Amjid Ali, Zulfiqar Ahmad Khan, Altaf Hussain +3
Anomaly recognition plays a vital role in surveillance, transportation, healthcare, and public safety. However, most existing approaches rely solely on visual data, making them unr…
Multi Camera Connected Vision System with Multi View Analytics: A Comprehensive Survey
Muhammad Munsif, Waqas Ahmad, Amjid Ali +3
Connected Vision Systems (CVS) are transforming a variety of applications, including autonomous vehicles, smart cities, surveillance, and human-robot interaction. These systems har…
Pseudo-Labeling Driven Refinement of Benchmark Object Detection Datasets via Analysis of Learning Patterns
Min Je Kim, Muhammad Munsif, Altaf Hussain +2
Benchmark object detection (OD) datasets play a pivotal role in advancing computer vision applications such as autonomous driving, and surveillance, as well as in training and eval…