54 citations · 68 across the 41 of their papers we have counts for
14 papers · 1 filter
Elastic Token Compression for Pixel-Space Diffusion Transformers
Eduard Zamfir, Christian Reisswig, Zongwei Wu +2
Natural images concentrate their detail in a small fraction of the frame, yet diffusion models spend a full token on every patch, in every layer and at every timestep. The waste is…
When Simplicity Wins: Bottleneck-Aware Context Modeling for Lightweight Semantic Segmentation
Mian Muhammad Naeem Abid, Nancy Mehta, Zongwei Wu +1
Semantic segmentation demands a careful balance between accuracy, efficiency, and scalability, which remains difficult to achieve for high-resolution imagery. Convolutional network…
Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning
Yuqi Li, Yuedong Tan, Huiran Duan +7
Unified multimodal object tracking has achieved remarkable robustness by leveraging complementary sensor data (e.g., RGB, Thermal, Depth), yet the heavy computational burden of sta…
TRaM-VSR: Importance-Aware Token Routing and Merging for One-Step Diffusion Video Super-Resolution
Sicheng Gao, Zhuyun Zhou, Yixuan Liu +3
Video super-resolution (VSR) using large-scale Diffusion Transformer (DiT) priors achieves exceptional perceptual quality but is often impractical due to the quadratic computationa…
NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
Xin Li, Yeying Jin, Suhang Yao +95
This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success of the first edition, this c…
The First Controllable Bokeh Rendering Challenge at NTIRE 2026
Tim Seizinger, Florin-Alexandru Vasluianu, Jeffrey Chen +23
This study presents the outcomes of the first Controllable Bokeh Rendering Challenge at NTIRE and highlights the most effective submitted methodologies. In total, 44 participants r…
NTIRE 2026 Challenge on Efficient Low Light Image Enhancement: Methods and Results
Jiebin Yan, Chenyu Tu, Weixia Zhang +8
This paper presents a comprehensive review of the NITRE 2026 Efficient Low Light Image Enhancement (E-LLIE) Challenge, highlighting the proposed solutions and final outcomes. This…
Specialist-Generalist Fusion with Outcome-Supervised Rationales for Deepfake Detection
Benedikt Hopf, Zongwei Wu, Radu Timofte
Generalizable deepfake detection requires complementary forensic and semantic visual evidence. Specialist encoders capture subtle manipulation traces but can overfit to source-spec…
Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark
Yiting Wang, Nolwenn Peyratout, Tim Brodermann +13
This paper presents the report of the URVIS 2026 challenge on adverse-to-extreme panoptic segmentation. As the first challenge of its kind, it attracted 17 registered participants…
NTIRE 2026 Challenge on Bitstream-Corrupted Video Restoration: Methods and Results
Wenbin Zou, Tianyi Liu, Kejun Wu +37
This paper reports on the NTIRE 2026 Challenge on Bitstream-Corrupted Video Restoration (BSCVR). The challenge aims to advance research on recovering visually coherent videos from…
The Second Challenge on Cross-Domain Few-Shot Object Detection at NTIRE 2026: Methods and Results
Xingyu Qiu, Yuqian Fu, Jiawei Geng +70
Cross-domain few-shot object detection (CD-FSOD) remains a challenging problem for existing object detectors and few-shot learning approaches, particularly when generalizing across…
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…
Language-Free Generative Editing from One Visual Example
Omar Elezabi, Eduard Zamfir, Zongwei Wu +1
Text-guided diffusion models have advanced image editing by enabling intuitive control through language. However, despite their strong capabilities, we surprisingly find that SOTA…
Video Understanding: From Geometry and Semantics to Unified Models
Zhaochong An, Zirui Li, Mingqiao Ye +9
Video understanding aims to enable models to perceive, reason about, and interact with the dynamic visual world. In contrast to image understanding, video understanding inherently…