Yibo Wang, Xun Cao, Bihan Wen, Kailai Zhou, Lijing Cai, Mengya Zhang, Qiu Shen
We lifted 4 functions out of this paper's own repositories and ran 3 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| CalayZhou/JDM-HDRNet | canonical | 3 of 4 |
| Function | Status | Where it lives |
|---|---|---|
| conv_layer | Ran | CalayZhou/JDM-HDRNet/layers.py code served (permissive licence) · get_code("65a1da76a11d98de") |
| f_score | Ran | CalayZhou/JDM-HDRNet/segmentation-jdm/mmseg/core/evaluation/metrics.py code served (permissive licence) · get_code("f45b38ab7d505aa7") |
| fc_layer | Ran | CalayZhou/JDM-HDRNet/layers.py code served (permissive licence) · get_code("ecb3cf457108184f") |
| slicing | Not yet run | CalayZhou/JDM-HDRNet/layers.py code served (permissive licence) · get_code("f46d6c163e94167e") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
The integration of miniaturized spectrometers into mobile devices offers new avenues for image quality enhancement and facilitates novel downstream tasks. However, the broader application of spectral sensors in mobile photography is hindered by the inherent complexity of spectral images and the constraints of spectral imaging capabilities. To overcome these challenges, we propose a joint RGB-Spectral decomposition model guided enhancement framework, which consists of two steps: joint decomposition and prior-guided enhancement. Firstly, we leverage the complementarity between RGB and Low-resolution Multi-Spectral Images (Lr-MSI) to predict shading, reflectance, and material semantic priors. Subsequently, these priors are seamlessly integrated into the established HDRNet to promote dynamic range enhancement, color mapping, and grid expert learning, respectively. Additionally, we construct a high-quality Mobile-Spec dataset to support our research, and our experiments validate the effectiveness of Lr-MSI in the tone enhancement task. This work aims to establish a solid foundation for advancing spectral vision in mobile photography. The code is available at https://github.com/CalayZhou/JDM-HDRNet.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2407.17996")
get_code_for_paper("2407.17996")
have("2407.17996")
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