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Record W3048574953 · doi:10.1145/3388763.3407759

3D Sketching for Multi-Pose Products: An Interactive Showcase

2020· article· en· W3048574953 on OpenAlexaff
Joon Hyub Lee, Hyung-Gi Ham, Myung-Sung Kim, Seok-Hyung Bae

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInteractive and Immersive Displays
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsSketchPerspective (graphical)Computer scienceHuman–computer interactionObject (grammar)Interactive designArtificial intelligence

Abstract

fetched live from OpenAlex

2D perspective sketching is an essential tool for designers during the early stage of design. However, for products that have moving parts and take different poses during usage, 2D perspective sketching can be painstaking and time-consuming. In this interactive showcase, we present a 3D sketching system for multi-pose products. Our system lets designers easily sketch 3D curves, and part, rig, and pose them. We showcase that, with interactions that closely resemble traditional 2D perspective sketching and the physical manipulation of an articulated object, designers can quickly try many different form and movement ideas in 3D during the early stage of design.

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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.784
Threshold uncertainty score0.520

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 communication0.0000.002
Open science0.0010.000
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 head0.078
GPT teacher head0.333
Teacher spread0.255 · 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
GenreMethods

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

Citations3
Published2020
Admission routes1
Has abstractyes

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