354 citations · 357 across the 12 of their papers we have counts for
7 papers · 1 filter
The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results
Jingkai Wang, Jue Gong, Zheng Chen +50
This paper provides a review of the NTIRE 2026 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on ge…
NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results
Xin Li, Jiachao Gong, Xijun Wang +75
This paper presents an overview of the NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models. This challenge utilizes a new short-form UGC (S-…
EfficientSAM3: Progressive Hierarchical Distillation for Video Concept Segmentation from SAM1, 2, and 3
Chengxi Zeng, Yuxuan Jiang, Aaron Zhang
The Segment Anything Model 3 (SAM3) advances visual understanding with Promptable Concept Segmentation (PCS) across images and videos, but its unified architecture (shared vision b…
Agglomerating Large Vision Encoders via Distillation for VFSS Segmentation
Chengxi Zeng, Yuxuan Jiang, Fan Zhang +2
The deployment of foundation models for medical imaging has demonstrated considerable success. However, their training overheads associated with downstream tasks remain substantial…
C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scales
Yuxuan Jiang, Chengxi Zeng, Siyue Teng +4
In recent years, attention mechanisms have been exploited in single image super-resolution (SISR), achieving impressive reconstruction results. However, these advancements are stil…
Tuning Vision Foundation Model via Test-Time Prompt-Guided Training for VFSS Segmentations
Chengxi Zeng, David Smithard, Alberto M Gambaruto +1
Vision foundation models have demonstrated exceptional generalization capabilities in segmentation tasks for both generic and specialized images. However, a performance gap persist…
Video-SwinUNet: Spatio-temporal Deep Learning Framework for VFSS Instance Segmentation
Chengxi Zeng, Xinyu Yang, David Smithard +3
This paper presents a deep learning framework for medical video segmentation. Convolution neural network (CNN) and transformer-based methods have achieved great milestones in medic…