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Found 6 papers, 4 papers with code
Image Enhancement Based on Histogram-Guided Multiple Transformation Function Estimation
Next, we estimate multiple transformation functions utilizing a cross-attention block to capture the relevance between spatial and statistical information in the input image and its histogram, respectively.
Ranked #2 on
Image Enhancement
on MIT-Adobe 5k
(PSNR on proRGB metric)
Multiple transformation function estimation for image enhancement
First, we develop a histogram-based multiple transformation function estimation network (HMTF-Net) to estimate multiple transformation functions by exploiting both the spatial and statistical information of the input images.
Ranked #7 on
Image Enhancement
on MIT-Adobe 5k
(PSNR on proRGB metric)
Cross-modal transformers for infrared and visible image fusion
In this work, we propose a cross-modal transformer-based fusion (CMTFusion) algorithm for infrared and visible image fusion that captures global interactions by faithfully extracting complementary information from source images.
Exposure-Aware Dynamic Weighted Learning for Single-Shot HDR Imaging
We propose a novel single-shot high dynamic range (HDR) imaging algorithm based on exposure-aware dynamic weighted learning, which reconstructs an HDR image from a spatially varying exposure (SVE) raw image.
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).
NTIRE 2020 Challenge on Image Demoireing: Methods and Results
Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image.
