# A Dual Camera System for High Spatiotemporal Resolution Video Acquisition

arXiv: https://arxiv.org/abs/1909.13051 · HTML: https://mlsanity.com/paper/1909.13051/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Sep 2019.

## Built on by (most cited first, 7 of 7)

- [Capturing Stable HDR Videos Using a Dual-Camera System](https://mlsanity.com/paper/2507.06593/) (2025)
- [NeuriCam: Key-Frame Video Super-Resolution and Colorization for IoT Cameras](https://mlsanity.com/paper/2207.12496/) (2022)
- [Prediction-assistant Frame Super-Resolution for Video Streaming](https://mlsanity.com/paper/2103.09455/) (2021)
- [H2-Stereo: High-Speed, High-Resolution Stereoscopic Video System](https://mlsanity.com/paper/2208.02436/) (2022)
- [HSTR-Net: High Spatio-Temporal Resolution Video Generation For Wide Area Surveillance](https://mlsanity.com/paper/2204.04435/) (2022)
- [HSTR-Net: Reference Based Video Super-resolution with Dual Cameras](https://mlsanity.com/paper/2310.12092/) (2023)
- [How to Design a Compact High-Throughput Video Camera?](https://mlsanity.com/paper/2604.10619/) (2026)

## Abstract (arXiv)

This paper presents a dual camera system for high spatiotemporal resolution (HSTR) video acquisition, where one camera shoots a video with high spatial resolution and low frame rate (HSR-LFR) and another one captures a low spatial resolution and high frame rate (LSR-HFR) video. Our main goal is to combine videos from LSR-HFR and HSR-LFR cameras to create an HSTR video. We propose an end-to-end learning framework, AWnet, mainly consisting of a FlowNet and a FusionNet that learn an adaptive weighting function in pixel domain to combine inputs in a frame recurrent fashion. To improve the reconstruction quality for cameras used in reality, we also introduce noise regularization under the same framework. Our method has demonstrated noticeable performance gains in terms of both objective PSNR measurement in simulation with different publicly available video and light-field datasets and subjective evaluation with real data captured by dual iPhone 7 and Grasshopper3 cameras. Ablation studies are further conducted to investigate and explore various aspects (such as reference structure, camera parallax, exposure time, etc) of our system to fully understand its capability for potential applications.