MétaCan
Menu
Back to cohort
Record W2346394592 · doi:10.1145/2851581.2889433

Sketching Stylized Animated Drawings with Motion Amplifiers

2016· article· en· W2346394592 on OpenAlexaff
Rubaiat Habib Kazi, Tovi Grossman, Nobuyuki Umetani, George Fitzmaurice

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHuman Motion and Animation
Canadian institutionsAutodesk (Canada)
Fundersnot available
KeywordsStylized factComputer graphics (images)Computer scienceMotion (physics)AnimationNon-photorealistic renderingComputer visionComputer animationArtificial intelligenceComputer facial animation

Abstract

fetched live from OpenAlex

We present a sketching tool for crafting animated illustrations that contain the exaggerated dynamics of stylized 2D animations. Our 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. Our system leverages the freeform nature of sketching, allowing users to rapidly sketch, record motion, explore exaggerated dynamics using the amplifiers, and fine-tune their animations.

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.

How this classification was reachedexpand

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.515
Threshold uncertainty score0.793

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)0.0010.000

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 head0.006
GPT teacher head0.175
Teacher spread0.169 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicHuman Motion and AnimationFrench-language works237,207