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Stabilisation Input — pan-city, Rotational roll

Rotational roll camera shake applied to the locked-off pan-city plate: up to 4.0 px of translation and 1.6° of roll at 8.0 Hz, seed 5162. Translation plus up to 1.6° of roll. Translation-only stabilisers cannot fix roll at all, so this immediately separates 2-DOF from full-affine implementations. Uncovered edges are filled black rather than padded, so the crop a stabiliser needs is visible in the input.

File: MP4 · Stab · 640x360
Use case: Video stabilisationVideo QA· Conversion set

Stabilisation Input — text-motion, Heavy handheld

Heavy handheld camera shake applied to the locked-off text-motion plate: up to 12.0 px of translation at 6.5 Hz, seed 5131. Twelve-pixel excursions at a slower, larger cadence: running, or a long lens. Requires real trajectory smoothing rather than frame-to-frame alignment. Uncovered edges are filled black rather than padded, so the crop a stabiliser needs is visible in the input.

File: MP4 · Stab · 640x360
Use case: Video stabilisationVideo QA· Conversion set

Stabilisation Input — text-motion, High-frequency jitter

High-frequency jitter camera shake applied to the locked-off text-motion plate: up to 2.5 px of translation and 0.5° of roll at 23.0 Hz, seed 5193. Small, fast jitter near the frame rate — vibration from a vehicle or a drone motor. Aliases against the sampling rate, so naive low-pass smoothing of the path leaves it almost untouched. Uncovered edges are filled black rather than padded, so the crop a stabiliser needs is visible in the input.

File: MP4 · Stab · 640x360
Use case: Video stabilisationVideo QA· Conversion set

Stabilisation Input — text-motion, Light handheld

Light handheld camera shake applied to the locked-off text-motion plate: up to 3.0 px of translation at 11.0 Hz, seed 5100. Sub-pixel-to-3-pixel translation at walking cadence — the residual wobble left after in-body stabilisation. Easy to correct, and the case where over-correction visibly crops the frame for nothing. Uncovered edges are filled black rather than padded, so the crop a stabiliser needs is visible in the input.

File: MP4 · Stab · 640x360
Use case: Video stabilisationVideo QA· Conversion set

Stabilisation Input — text-motion, Rotational roll

Rotational roll camera shake applied to the locked-off text-motion plate: up to 4.0 px of translation and 1.6° of roll at 8.0 Hz, seed 5162. Translation plus up to 1.6° of roll. Translation-only stabilisers cannot fix roll at all, so this immediately separates 2-DOF from full-affine implementations. Uncovered edges are filled black rather than padded, so the crop a stabiliser needs is visible in the input.

File: MP4 · Stab · 640x360
Use case: Video stabilisationVideo QA· Conversion set

Super-Resolution Ground Truth — detail-chart

The full-resolution reference for the detail-chart super-resolution set at 640x360. Every low-resolution input in this group was produced by downscaling these exact pixels with a recorded filter, so an upscaler's output can be compared against the true original instead of against another upscale.

File: MP4 · Superres · 640x360
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Ground Truth — pan-city

The full-resolution reference for the pan-city super-resolution set at 640x360. Every low-resolution input in this group was produced by downscaling these exact pixels with a recorded filter, so an upscaler's output can be compared against the true original instead of against another upscale.

File: MP4 · Superres · 640x360
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Ground Truth — text-motion

The full-resolution reference for the text-motion super-resolution set at 640x360. Every low-resolution input in this group was produced by downscaling these exact pixels with a recorded filter, so an upscaler's output can be compared against the true original instead of against another upscale.

File: MP4 · Superres · 640x360
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷2 Area / box

The detail-chart plate downscaled 2× to 320x180 using a area / box filter. Simple pixel averaging, what a camera's binning path actually does. Softer than bicubic and not what most models saw in training, which makes it a fairer test. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 320x180
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷2 Bicubic

The detail-chart plate downscaled 2× to 320x180 using a bicubic filter. The standard downscale in most benchmarks. Mild ringing at edges, and the filter most super-resolution models are trained to invert — so it flatters them. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 320x180
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷2 Nearest neighbour

The detail-chart plate downscaled 2× to 320x180 using a nearest neighbour filter. Point sampling with no filtering at all, so downscaling aliases hard. The Siemens star folds into moiré, and no amount of upscaling can recover what aliasing destroyed. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 320x180
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷3 Area / box

The detail-chart plate downscaled 3× to 212x120 using a area / box filter. Simple pixel averaging, what a camera's binning path actually does. Softer than bicubic and not what most models saw in training, which makes it a fairer test. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 212x120
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷3 Bicubic

The detail-chart plate downscaled 3× to 212x120 using a bicubic filter. The standard downscale in most benchmarks. Mild ringing at edges, and the filter most super-resolution models are trained to invert — so it flatters them. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 212x120
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷3 Nearest neighbour

The detail-chart plate downscaled 3× to 212x120 using a nearest neighbour filter. Point sampling with no filtering at all, so downscaling aliases hard. The Siemens star folds into moiré, and no amount of upscaling can recover what aliasing destroyed. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 212x120
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷4 Area / box

The detail-chart plate downscaled 4× to 160x90 using a area / box filter. Simple pixel averaging, what a camera's binning path actually does. Softer than bicubic and not what most models saw in training, which makes it a fairer test. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 160x90
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷4 Bicubic

The detail-chart plate downscaled 4× to 160x90 using a bicubic filter. The standard downscale in most benchmarks. Mild ringing at edges, and the filter most super-resolution models are trained to invert — so it flatters them. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 160x90
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — detail-chart, ÷4 Nearest neighbour

The detail-chart plate downscaled 4× to 160x90 using a nearest neighbour filter. Point sampling with no filtering at all, so downscaling aliases hard. The Siemens star folds into moiré, and no amount of upscaling can recover what aliasing destroyed. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 160x90
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — pan-city, ÷2 Area / box

The pan-city plate downscaled 2× to 320x180 using a area / box filter. Simple pixel averaging, what a camera's binning path actually does. Softer than bicubic and not what most models saw in training, which makes it a fairer test. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 320x180
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — pan-city, ÷2 Bicubic

The pan-city plate downscaled 2× to 320x180 using a bicubic filter. The standard downscale in most benchmarks. Mild ringing at edges, and the filter most super-resolution models are trained to invert — so it flatters them. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 320x180
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — pan-city, ÷2 Nearest neighbour

The pan-city plate downscaled 2× to 320x180 using a nearest neighbour filter. Point sampling with no filtering at all, so downscaling aliases hard. The Siemens star folds into moiré, and no amount of upscaling can recover what aliasing destroyed. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 320x180
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — pan-city, ÷3 Area / box

The pan-city plate downscaled 3× to 212x120 using a area / box filter. Simple pixel averaging, what a camera's binning path actually does. Softer than bicubic and not what most models saw in training, which makes it a fairer test. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 212x120
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — pan-city, ÷3 Bicubic

The pan-city plate downscaled 3× to 212x120 using a bicubic filter. The standard downscale in most benchmarks. Mild ringing at edges, and the filter most super-resolution models are trained to invert — so it flatters them. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 212x120
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — pan-city, ÷3 Nearest neighbour

The pan-city plate downscaled 3× to 212x120 using a nearest neighbour filter. Point sampling with no filtering at all, so downscaling aliases hard. The Siemens star folds into moiré, and no amount of upscaling can recover what aliasing destroyed. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 212x120
Use case: Video upscalingVideo QA· Conversion set

Super-Resolution Input — pan-city, ÷4 Area / box

The pan-city plate downscaled 4× to 160x90 using a area / box filter. Simple pixel averaging, what a camera's binning path actually does. Softer than bicubic and not what most models saw in training, which makes it a fairer test. Upscale it back to 640x360 and score against the ground truth in this group — the filter is recorded because which one was used changes the difficulty far more than the scale factor does.

File: MP4 · Superres · 160x90
Use case: Video upscalingVideo QA· Conversion set

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