# Ultra-High-Definition Dynamic Multi-Exposure Image Fusion via Infinite Pixel Learning

arXiv: https://arxiv.org/abs/2412.11685 · HTML: https://mlsanity.com/paper/2412.11685/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 28 references that are in the map.
- First posted on arXiv 16 Dec 2024.

## Builds on (most cited first, 11 of 11)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [MLP-Mixer: An all-MLP Architecture for Vision](https://mlsanity.com/paper/2105.01601/) (2021)
- [Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs](https://mlsanity.com/paper/2310.01801/) (2023)
- [Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method](https://mlsanity.com/paper/2212.11548/) (2022)
- [PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference](https://mlsanity.com/paper/2405.12532/) (2024)
- [Attention-guided Network for Ghost-free High Dynamic Range Imaging](https://mlsanity.com/paper/1904.10293/) (2019)
- [Ghost-free High Dynamic Range Imaging with Context-aware Transformer](https://mlsanity.com/paper/2208.05114/) (2022)
- [Correlation Matching Transformation Transformers for UHD Image Restoration](https://mlsanity.com/paper/2406.00629/) (2024)
- [Alignment-free HDR Deghosting with Semantics Consistent Transformer](https://mlsanity.com/paper/2305.18135/) (2023)
- [Exposure Bracketing Is All You Need For A High-Quality Image](https://mlsanity.com/paper/2401.00766/) (2024)

## Built on by (most cited first, 3 of 3)

- [Latent Harmony: Synergistic Unified UHD Image Restoration via Latent Space Regularization and Controllable Refinement](https://mlsanity.com/paper/2510.07961/) (2025)
- [Decouple to Reconstruct: High Quality UHD Restoration via Active Feature Disentanglement and Reversible Fusion](https://mlsanity.com/paper/2503.12764/) (2025)
- [UHD Image Dehazing via anDehazeFormer with Atmospheric-aware KV Cache](https://mlsanity.com/paper/2505.14010/) (2025)

## Abstract (arXiv)

With the continuous improvement of device imaging resolution, the popularity of Ultra-High-Definition (UHD) images is increasing. Unfortunately, existing methods for fusing multi-exposure images in dynamic scenes are designed for low-resolution images, which makes them inefficient for generating high-quality UHD images on a resource-constrained device. To alleviate the limitations of extremely long-sequence inputs, inspired by the Large Language Model (LLM) for processing infinitely long texts, we propose a novel learning paradigm to achieve UHD multi-exposure dynamic scene image fusion on a single consumer-grade GPU, named Infinite Pixel Learning (IPL). The design of our approach comes from three key components: The first step is to slice the input sequences to relieve the pressure generated by the model processing the data stream; Second, we develop an attention cache technique, which is similar to KV cache for infinite data stream processing; Finally, we design a method for attention cache compression to alleviate the storage burden of the cache on the device. In addition, we provide a new UHD benchmark to evaluate the effectiveness of our method. Extensive experimental results show that our method maintains high-quality visual performance while fusing UHD dynamic multi-exposure images in real-time (>40fps) on a single consumer-grade GPU.