mlsanityData to 14 Oct 2026

3R-INN: How to be climate friendly while consuming/delivering videos?

arXiv 2403.11760 ↗First posted 18 Mar 2024eess.IV cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

The consumption of a video requires a considerable amount of energy during the various stages of its life-cycle. With a billion hours of video consumed daily, this contributes significantly to the greenhouse gas emission. Therefore, reducing the end-to-end carbon footprint of the video chain, while preserving the quality of experience at the user side, is of high importance. To contribute in an impactful manner, we propose 3R-INN, a single light invertible network that does three tasks at once: given a high-resolution grainy image, it Rescales it to a lower resolution, Removes film grain and Reduces its power consumption when displayed. Providing such a minimum viable quality content contributes to reducing the energy consumption during encoding, transmission, decoding and display. 3R-INN also offers the possibility to restore either the high-resolution grainy original image or a grain-free version, thanks to its invertibility and the disentanglement of the high frequency, and without transmitting auxiliary data. Experiments show that, while enabling significant energy savings for encoding (78%), decoding (77%) and rendering (5% to 20%), 3R-INN outperforms state-of-the-art film grain synthesis and energy-aware methods and achieves state-of-the-art performance on the rescaling task on different test-sets.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 13 of its 41 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

13 of 41 references.

References · 13

  1. 2016Densely Connected Convolutional Networkscited by 6,720
  2. 2016Density estimation using Real NVPcited by 2,042
  3. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,545
  4. 2019On the Convergence of Adam and Beyondcited by 841
  5. 2020Invertible Image Rescalingcited by 92
  6. 2021Invertible Denoising Network: A Light Solution for Real Noise Removalcited by 68
  7. 2019Learned Image Downscaling for Upscaling using Content Adaptive Resamplercited by 55
  8. 2016Blind Image Denoising via Dependent Dirichlet Process Treecited by 5
  9. 2022Deep-based Film Grain Removal and Synthesiscited by 5
  10. 2020Versatile video coding and super-resolution for efficient delivery of 8K video with 4K backward-compatibilitycited by 3
  11. 2022Sweet Streams are Made of This: The System Engineer's View on Energy Efficiency in Video Communicationscited by 2
  12. 2023Invertible Mosaic Image Hiding Network for Very Large Capacity Image Steganographycited by 2
1 more
  1. 2023Hierarchical Disentangled Representation for Invertible Image Denoising and Beyondcited by 1

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.