mlsanityData to 14 Oct 2026

MIPI 2023 Challenge on Nighttime Flare Removal: Methods and Results

arXiv 2305.13770 ↗First posted 23 May 2023cs.CV eess.IVcited by 6

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Abstract (arXiv)

Developing and integrating advanced image sensors with novel algorithms in camera systems are prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). With the success of the 1st MIPI Workshop@ECCV 2022, we introduce the second MIPI challenge including four tracks focusing on novel image sensors and imaging algorithms. In this paper, we summarize and review the Nighttime Flare Removal track on MIPI 2023. In total, 120 participants were successfully registered, and 11 teams submitted results in the final testing phase. The developed solutions in this challenge achieved state-of-the-art performance on Nighttime Flare Removal. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found at https://mipi-challenge.org/MIPI2023/ .

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 24 of its 30 references that are in the map. First posted on arXiv 23 May 2023.

Builds on

24 of 30 references.

References · 24

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12 more
  1. 2021Aggregated Contextual Transformations for High-Resolution Image Inpaintingcited by 89
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 3; 2025: 1; 2026: 1.

6 papers.

  1. 2023Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolutioncited by 39
  2. 2024MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Resultscited by 11
  3. 2024MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Resultscited by 6
  4. 2024MIPI 2024 Challenge on Nighttime Flare Removal: Methods and Resultscited by 2
  5. 2025Clear Roads, Clear Vision: Advancements in Multi-Weather Restoration for Smart Transportationcited by 1
  6. 2026Semi-LAR: Semi-supervised Contrastive Learning with Linear Attention for Removal of Nighttime Flarescited by 0