# The First Controllable Bokeh Rendering Challenge at NTIRE 2026

arXiv: https://arxiv.org/abs/2605.05510 · HTML: https://mlsanity.com/paper/2605.05510/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 43 of its 75 references that are in the map.
- First posted on arXiv 6 May 2026.

## Builds on (most cited first, 30 of 43)

- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Score-Based Generative Modeling through Stochastic Differential Equations](https://mlsanity.com/paper/2011.13456/) (2020)
- [Masked Autoencoders Are Scalable Vision Learners](https://mlsanity.com/paper/2111.06377/) (2021)
- [FiLM: Visual Reasoning with a General Conditioning Layer](https://mlsanity.com/paper/1709.07871/) (2017)
- [Depth Anything V2](https://mlsanity.com/paper/2406.09414/) (2024)
- [Simple Baselines for Image Restoration](https://mlsanity.com/paper/2204.04676/) (2022)
- [Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis](https://mlsanity.com/paper/2505.09358/) (2025)
- [Synthetic Depth-of-Field with a Single-Camera Mobile Phone](https://mlsanity.com/paper/1806.04171/) (2018)
- [Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking Platform](https://mlsanity.com/paper/2110.05802/) (2021)
- [Rendering Natural Camera Bokeh Effect with Deep Learning](https://mlsanity.com/paper/2006.05698/) (2020)
- [Seven ways to improve example-based single image super resolution](https://mlsanity.com/paper/1511.02228/) (2015)
- [BokehMe: When Neural Rendering Meets Classical Rendering](https://mlsanity.com/paper/2206.12614/) (2022)
- [Fast Deep Matting for Portrait Animation on Mobile Phone](https://mlsanity.com/paper/1707.08289/) (2017)
- [Synthetic Defocus and Look-Ahead Autofocus for Casual Videography](https://mlsanity.com/paper/1905.06326/) (2019)
- [AIM 2020 Challenge on Rendering Realistic Bokeh](https://mlsanity.com/paper/2011.04988/) (2020)
- [SteReFo: Efficient Image Refocusing with Stereo Vision](https://mlsanity.com/paper/1909.13395/) (2019)
- [The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report](https://mlsanity.com/paper/2604.03198/) (2026)
- [Stacked Deep Multi-Scale Hierarchical Network for Fast Bokeh Effect Rendering from a Single Image](https://mlsanity.com/paper/2105.07174/) (2021)
- [NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild](https://mlsanity.com/paper/2604.11487/) (2026)
- [MPIB: An MPI-Based Bokeh Rendering Framework for Realistic Partial Occlusion Effects](https://mlsanity.com/paper/2207.08403/) (2022)
- [NTIRE 2026 Challenge on Bitstream-Corrupted Video Restoration: Methods and Results](https://mlsanity.com/paper/2604.06945/) (2026)
- [NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Multi-Exposure Image Fusion in Dynamic Scenes (Track 2)](https://mlsanity.com/paper/2604.09030/) (2026)
- [NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods](https://mlsanity.com/paper/2604.10321/) (2026)
- [NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results](https://mlsanity.com/paper/2604.10551/) (2026)
- [NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results](https://mlsanity.com/paper/2604.10634/) (2026)
- [The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results](https://mlsanity.com/paper/2604.10532/) (2026)
- [The Second Challenge on Cross-Domain Few-Shot Object Detection at NTIRE 2026: Methods and Results](https://mlsanity.com/paper/2604.11998/) (2026)
- [NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)](https://mlsanity.com/paper/2604.11230/) (2026)
- [NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)](https://mlsanity.com/paper/2604.12512/) (2026)
- [Bokehlicious: Photorealistic Bokeh Rendering with Controllable Apertures](https://mlsanity.com/paper/2503.16067/) (2025)

## Built on by (most cited first, 2 of 2)

- [The Third Challenge on Image Denoising at NTIRE 2026: Methods and Results](https://mlsanity.com/paper/2606.16031/) (2026)
- [NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge](https://mlsanity.com/paper/2608.09782/) (2026)

## Abstract (arXiv)

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 registered for the competition, of which 8 teams submitted valid solutions after the conclusion of the final test phase. All submissions were evaluated on unseen images, focusing on portraits and intricate subjects with complex and visually appealing bokeh phenomena. In addition to the first track focusing on established quantitative fidelity metrics, we conducted a qualitative user study with a panel of experts for a second track focusing on perceptual assessment. As this was the inaugural challenge on this topic, most of the participants focused on refining and extending the Bokehlicious baseline method.