Research map / Video / Video segmentation and tracking
Learning To Reconstruct High Speed and High Dynamic Range Videos From Events
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the proposed recurrent event-to-HDR reconstruction method instead of EF | Event-to-HDR video reconstruction · Simulated data | PSNR: 13.23 -> 15.31 | Helped |
| Use the proposed recurrent event-to-HDR reconstruction method instead of EF | Event-to-HDR video reconstruction · Simulated data | SSIM: 0.5914 -> 0.7084 | Helped |
| Use the proposed recurrent event-to-HDR reconstruction method instead of EF | Event-to-HDR video reconstruction · Simulated data | LPIPS: 0.3030 -> 0.2424 | Helped |
| Use the proposed recurrent event-to-HDR reconstruction method instead of EF | Event-to-HDR video reconstruction · Simulated data | TC: 0.9729 -> 0.5198 | Helped |
| Use the proposed recurrent event-to-HDR reconstruction method instead of EF | Event-to-HDR video reconstruction · Real data | PSNR: 14.77 -> 16.41 | Helped |
| Use the proposed recurrent event-to-HDR reconstruction method instead of E2VID | Event-to-HDR video reconstruction · Real data | SSIM: 0.4781 -> 0.4783 | No clear effect |
| Use the proposed recurrent event-to-HDR reconstruction method instead of E2VID | Event-to-HDR video reconstruction · Real data | LPIPS: 0.4200 -> 0.3737 | Helped |
| Use the proposed recurrent event-to-HDR reconstruction method instead of EF | Event-to-HDR video reconstruction · Real data | TC: 0.4191 -> 0.3539 | Helped |
| Add the ConvLSTM recurrent module (ablation) | Proposed method · Simulated data | PSNR: 14.71 -> 15.31 | Helped |
| Add the ConvLSTM recurrent module (ablation) | Proposed method · Simulated data | SSIM: 0.6362 -> 0.7084 | Helped |
| Add temporal consistency loss (ablation) | Proposed method · Simulated data | TC: 0.5549 -> 0.5198 | Helped |
| Add temporal consistency loss (ablation) | Proposed method · Simulated data | LPIPS: 0.2455 -> 0.2424 | Helped |
Closest papers by meaning
- Learning Event Guided High Dynamic Range Video Reconstruction (CVPR 2023 · similarity 0.91)
- EvHDR-GS: Event-guided HDR Video Reconstruction with 3D Gaussian Splatting (AAAI 2025 · similarity 0.88)
- E2HQV: High-Quality Video Generation from Event Camera via Theory-Inspired Model-Aided Deep Learning (AAAI 2024 · similarity 0.88)
- Towards Real-World HDR Video Reconstruction: A Large-Scale Benchmark Dataset and A Two-Stage Alignment Network (CVPR 2024 · similarity 0.87)
- HDRFlow: Real-Time HDR Video Reconstruction with Large Motions (CVPR 2024 · similarity 0.87)
- LaSe-E2V: Towards Language-guided Semantic-aware Event-to-Video Reconstruction (NeurIPS 2024 · similarity 0.87)
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