2 citations · 2 across the 1 of their papers we have counts for
7 papers
NTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Results
Zheng Chen, Kai Liu, Jue Gong +108
This paper presents the NTIRE 2025 image super-resolution (4) challenge, one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025. The challenge aims to r…
Low Light Image Enhancement Challenge at NTIRE 2026
George Ciubotariu, Sharif S M A, Abdur Rehman +90
This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final results. The objective of this cha…
Enhancing Mixture-of-Experts Specialization via Cluster-Aware Upcycling
Sanghyeok Chu, Pyunghwan Ahn, Gwangmo Song +3
Sparse Upcycling provides an efficient way to initialize a Mixture-of-Experts (MoE) model from pretrained dense weights instead of training from scratch. However, since all experts…
TIPSv2: Advancing Vision-Language Pretraining with Enhanced Patch-Text Alignment
Bingyi Cao, Koert Chen, Kevis-Kokitsi Maninis +16
Recent progress in vision-language pretraining has enabled significant improvements to many downstream computer vision applications, such as classification, retrieval, segmentation…
Towards Efficient Large Vision-Language Models: A Comprehensive Survey on Inference Strategies
Surendra Pathak, Bo Han
Although Large Vision Language Models (LVLMs) have demonstrated impressive multimodal reasoning capabilities, their scalability and deployment are constrained by massive computatio…
Beyond the Ground Truth: Enhanced Supervision for Image Restoration
Donghun Ryou, Inju Ha, Sanghyeok Chu +1
Deep learning-based image restoration has achieved significant success. However, when addressing real-world degradations, model performance is limited by the quality of groundtruth…