README.md

---
pretty_name: Sintel Low-light Noise ELD
license: apache-2.0
tags:
- optical-flow
- low-light
- noise
- synthetic-data
- sintel
- eld
- robustness
- video
- noise
- computer-vision
- image-sequence
- denoising
- video-frames
size_categories:
- 10K<n<100K
---
  # Sintel Low-light Noise ELD

  A synthetic low-light optical flow dataset derived from MPI Sintel using the `ELD` low-light noise preset.

  This dataset contains noisy RGB frames for both the `train` and `test` splits and is intended for:
  - optical flow robustness evaluation in low-light conditions
  - fine-tuning pretrained optical flow models
  - controlled experiments on synthetic low-light degradation

  ## Contents

  The dataset contains ELD-corrupted Sintel frames for:
  - training
  - test

  This dataset includes only the noisy ELD data.

  ## What This Dataset Is For

  This dataset is useful when you want to test or train optical flow models on darker, noisier Sintel-style inputs without changing the underlying scene
  content.

  Typical use cases:
  - compare model performance on standard vs low-light inputs
  - fine-tune a pretrained model for low-light robustness
  - benchmark robustness under synthetic low-light degradation

  ## Noise Model

  This dataset uses the `ELD` low-light noise model.

  The ELD corruption includes:
  - brightness reduction
  - shot noise
  - read noise
  - quantization noise
  - banding artifacts

  Compared with more aggressive synthetic corruption models, ELD generally produces more stable and visually plausible low-light results.

  ## Why Sintel + ELD?

  MPI Sintel is widely used for optical flow evaluation, but it does not natively include low-light variants.

  Applying ELD-style degradation provides:
  - a controlled robustness benchmark
  - the same scene/layout content as Sintel
  - a direct way to study low-light failure modes in optical flow

  ## Recommended Use

  Best use:
  - fine-tune a pretrained optical flow model
  - evaluate robustness to low-light corruption
  - compare against clean Sintel performance

  Less recommended:
  - treating this as real-world low-light ground truth
  - relying on it as the only low-light training source

  This dataset is synthetic and is best used for controlled experiments.

  ## File Structure

  ```
  Sintel-noisy/
    train/
      alley_1/
      alley_2/
      ...
    test/
      ambush_1/
      cave_3/
      ...

  ```    

  ## Notes

  - This dataset contains only the ELD noisy version.
  - It is a synthetic low-light corruption dataset, not a real capture dataset.
  - Transfer to real low-light video should be validated separately.


  ## Acknowledgements

  This dataset is derived from MPI Sintel and applies synthetic ELD low-light corruption to the original image content.

  Please respect the licensing terms of the original Sintel dataset.