MétaCan
Menu
Back to cohort
Record W2507127590 · doi:10.1145/2858036.2858386

Motion Amplifiers

2016· article· en· W2507127590 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsAutodesk (Canada)
Fundersnot available
KeywordsAnimationComputer scienceAmplifierSketchSet (abstract data type)Computer animationMotion (physics)Computer graphics (images)Stylized factHuman–computer interactionArtificial intelligenceBandwidth (computing)Programming languageTelecommunications

Abstract

fetched live from OpenAlex

We present a sketching tool for crafting animated illustrations that contain the exaggerated dynamics of stylized 2D animations. The system provides a set of motion amplifiers which implement a set of established principles of 2D animation. These amplifiers break down a complex animation effect into independent, understandable chunks. Each amplifier imposes deformations to an underlying grid, which in turn updates the corresponding strokes. Users can combine these amplifiers at will when applying them to an existing animation, promoting rapid experimentation. By leveraging the freeform nature of sketching, our system allows users to rapidly sketch, record motion, explore exaggerated dynamics using the amplifiers, and fine-tune their animations. Practical results confirm that users with no prior experience in animation can produce expressive animated illustrations quickly and easily.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.185
Teacher spread0.175 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations45
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicHuman Motion and AnimationFrench-language works237,207