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Record W4400763553 · doi:10.1145/3641233.3664347

Making of Chameleon Transformation FX in KFP4

2024· article· en· W4400763553 on OpenAlexaff
Zachary Glynn, Jinguang Huang, L. J. Gray, Hamid Shahsavari, Wang Zhao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsRealNetworks (Canada)
Fundersnot available
KeywordsTransformation (genetics)Computer science

Abstract

fetched live from OpenAlex

In the world of Kung Fu Panda 4, the transformation FX emerges as one of the central narrative elements, showcasing the primary power of the film’s key villain, the Chameleon. This effect imbues the character with a scary, unsettling, ability to morph into different forms, varying significantly in size and shape. It enhances the storytelling by allowing the chameleon to be ubiquitously present in various guises and places. Our FX team embarked on a journey to develop a robust transformation system capable of handling numerous characters. It had to be flexible enough to cater to the needs of a large group of artists and adaptable across a wide range of shots from dynamic kung fu action to close-ups with subtle camera movement. Additionally, this work involved cooperative efforts with multiple departments, such as animation, CFX and lighting, resulting in the creation of cross-department workflows.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.842
Threshold uncertainty score0.118

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)0.0000.000

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 head0.014
GPT teacher head0.234
Teacher spread0.220 · 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 designSimulation or modeling
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

Citations0
Published2024
Admission routes1
Has abstractyes

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