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jhakrraman avatar

jhakrraman/rt-xnet

0
View on GitHub↗
22 stars·0 forks·Python·MIT·9 viewsarxiv.org/abs/2505.24705↗

Rt Xnet

Raman Jha, Adithya Lenka, Mani Ramanagopal, Aswin Sankaranarayanan, Kaushik Mitra

Features

  • Deep Learning Methods - RGB-thermal cross-attention network for enhancement.
  • Retinex Based Methods - RGB-thermal cross attention network for enhancement.

Star history

Star history chart for jhakrraman/rt-xnetStar history chart for jhakrraman/rt-xnet

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Projects sharing features with Rt Xnet

These projects share indexed features with Rt Xnet. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • caiyuanhao1998/retinexformerC

    caiyuanhao1998/Retinexformer

    0View on GitHub↗
    View on GitHub↗0
  • chunminghe/reti-diffChunmingHe avatar

    ChunmingHe/Reti-Diff

    121View on GitHub↗

    ICLR2025 Spotlight ✨

    Python
    View on GitHub↗121
  • andersonyong/uretinex-netAndersonYong avatar

    AndersonYong/URetinex-Net

    226View on GitHub↗

    See URetinex-Net++. We release training code of URetinex-Net++, which share the decomposition module and unfolding module with URetinex-Net, enjoy!

    Python
    View on GitHub↗226
  • dut-media-lab/ruasdut-media-lab avatar

    dut-media-lab/RUAS

    37View on GitHub↗

    this is the official code for the paper "Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement"

    Python
    View on GitHub↗37
Compare all 30 related projects→

Frequently asked questions

What does jhakrraman/rt-xnet do?

Raman Jha, Adithya Lenka, Mani Ramanagopal, Aswin Sankaranarayanan, Kaushik Mitra

What are the main features of jhakrraman/rt-xnet?

The main features of jhakrraman/rt-xnet are: Deep Learning Methods, Retinex Based Methods.

Which projects share features with jhakrraman/rt-xnet?

Projects with overlapping indexed features include: chunminghe/reti-diff — ICLR2025 Spotlight ✨. weichen582/retinexnet — This is a Tensorflow implement of RetinexNet. andersonyong/uretinex-net — See URetinex-Net++. We release training code of URetinex-Net++, which share the decomposition module and unfolding… caiyuanhao1998/retinexformer —  . dut-media-lab/ruas — this is the official code for the paper "Retinex-inspired Unrolling with Cooperative Prior Architecture Search for… caibolun/jiep — Bolun Cai, Xianming Xu, Kailing Guo, Kui Jia, Bin Hu, Dacheng Tao.