eXtreme-Deformable (XD) Evaluation Dataset from gQIR: Generative Quanta Image Reconstruction

Aryan Garg¹, Sizhuo Ma², Mohit Gupta¹

¹ University of Wisconsin-Madison
² Snap, Inc

Interesting deformable physics scenes - explosions, shattering objects, bullets, fluids etc scraped from the internet. All the videos have been manually filtered for interesting content (subjective binary decision) and then processed: removed audio --> clipped --> resized. Each video is atleast 10 seconds or > 200-frames. See SPAD-Simulation-Pipeline for streaming the input to train/test models.

Credits to original creators with majority scrape results:

1. www.youtube.com/@theslowmoguys
2. www.youtube.com/@BallisticHighSpeed

NOTE: So far only paper + supplementary GT videos are added. Full dataset will be released gradually with outputs and more testing.

Tentative: June 1, 2026 for full XD-dataset release.

Please cite our dataset/work if you find it useful. Thanks! :)

@InProceedings{garg_2026_gqir,
    author    = {Garg, Aryan and Ma, Sizhuo and  Gupta, Mohit},
    title     = {gQIR: Generative Quanta Image Reconstruction},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2026},
}

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gQIR's code & weights are available at: Github & HF respectively.