mlsanityData to 14 Oct 2026

How to Design a Compact High-Throughput Video Camera?

arXiv 2604.10619 ↗First posted 12 Apr 2026cs.CVcited by 0

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Abstract (arXiv)

High throughput video acquisition is a challenging problem and has been drawing increasing attention. Existing high throughput imaging systems splice hundreds of sub-images/videos into high throughput videos, suffering from extremely high system complexity. Alternatively, with pixel sizes reducing to sub-micrometer levels, integrating ultra-high throughput on a single chip is becoming feasible. Nevertheless, the readout and output transmission speed cannot keep pace with the increasing pixel numbers. To this end, this paper analyzes the strength of gradient cameras in fast readout and efficient representation, and proposes a low-bit gradient camera scheme based on existing technologies that can resolve the readout and transmission bottlenecks for high throughput video imaging. A multi-scale reconstruction CNN is proposed to reconstruct high-resolution images. Extensive experiments on both simulated and real data are conducted to demonstrate the promising quality and feasibility of the proposed method.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 35 references that are in the map. First posted on arXiv 12 Apr 2026.

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12 of 35 references.

References · 12

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,908
  3. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,552
  4. 2018Image Super-Resolution Using Very Deep Residual Channel Attention Networkscited by 1,264
  5. 2016Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Networkcited by 1,204
  6. 2017Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolutioncited by 453
  7. 2019SinGAN: Learning a Generative Model from a Single Natural Imagecited by 348
  8. 2018Deep Back-Projection Networks For Super-Resolutioncited by 225
  9. 2018CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warpingcited by 91
  10. 2020Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolutioncited by 90
  11. 2020PANDA: A Gigapixel-level Human-centric Video Datasetcited by 45
  12. 2019A Dual Camera System for High Spatiotemporal Resolution Video Acquisitioncited by 7

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