2 citations · 3 across the 8 of their papers we have counts for
8 papers
Real-Time Video Anomaly Detection Using YOLO Pose Estimation and CLIP-Based Semantic Scoring
Vanodhya G. Warnasooriya, Amir Hajian, Watchara Ruangsang +1
We propose a lightweight two-stage framework for real-time video anomaly detection. The first stage employs YOLO v11n-pose to detect persons and extract seventeen skeletal keypoint…
Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation
Chaofan Gan, Zicheng Zhao, Yuanpeng Tu +6
Massive Activations (MAs) have been widely observed in Transformer-based models, yet their structure and functional roles in Diffusion Transformers (DiTs) remain insufficiently und…
The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
Jiatong Li, Zheng Chen, Kai Liu +91
This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge…
The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report
Bin Ren, Hang Guo, Yan Shu +60
This paper reviews the NTIRE 2026 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a…
MCA: 2D-3D Retrieval with Noisy Labels via Multi-level Adaptive Correction and Alignment
Gui Zou, Chaofan Gan, Chern Hong Lim +2
With the increasing availability of 2D and 3D data, significant advancements have been made in the field of cross-modal retrieval. Nevertheless, the existence of imperfect annotati…
Attention GhostUNet++: Enhanced Segmentation of Adipose Tissue and Liver in CT Images
Mansoor Hayat, Supavadee Aramvith, Subrata Bhattacharjee +1
Accurate segmentation of abdominal adipose tissue, including subcutaneous (SAT) and visceral adipose tissue (VAT), along with liver segmentation, is essential for understanding bod…
An Advanced Features Extraction Module for Remote Sensing Image Super-Resolution
Naveed Sultan, Amir Hajian, Supavadee Aramvith
In recent years, convolutional neural networks (CNNs) have achieved remarkable advancement in the field of remote sensing image super-resolution due to the complexity and variabili…
SEGSRNet for Stereo-Endoscopic Image Super-Resolution and Surgical Instrument Segmentation
Mansoor Hayat, Supavadee Aramvith, Titipat Achakulvisut
SEGSRNet addresses the challenge of precisely identifying surgical instruments in low-resolution stereo endoscopic images, a common issue in medical imaging and robotic surgery. Ou…