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

• URL: http://arxiv.org/abs/2412.11685v1
• Date: Mon, 16 Dec 2024 11:55:26 GMT
• Title: Ultra-High-Definition Dynamic Multi-Exposure Image Fusion via Infinite Pixel Learning
• Authors: Xingchi Chen, Zhuoran Zheng, Xuerui Li, Yuying Chen, Shu Wang, Wenqi Ren,
• Abstract summary: Existing methods for fusing multi-exposure images in dynamic scenes are designed for low-resolution images. We propose a novel learning paradigm to achieve UHD multi-exposure dynamic scene image fusion on a single consumer-grade GPU. Our method maintains high-quality visual performance while fusing UHD dynamic multi-exposure images in real-time.
• Score: 36.536727716387446
• License:
• Abstract: 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.

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