CurveCodec 2: Skeleton-agnostic animation compression with a learned entropy model
Overview
This research paper introduces CurveCodec 2, an animation compression system that achieves significant data reduction for skeletal motion. The method utilizes a learned entropy model to code residuals after quantizing curves in the log map and thinning them based on rate-distortion criteria. On a held-out test set of 4,472 clips from 33 datasets, CurveCodec 2 requires only 0.37x the bytes of the industry-standard ACL library at its default precision (0.01 cm) under a worst-case error contract, while decoding on a single CPU core and transferring without retraining to unseen skeleton types.
Generated from attributed reports · Updated 2 hours ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Reported quantity · bytes: 0.37 other · Basis not reported · Differing source assertions
“odec 2 needs 0.37x ACL's bytes at ACL's default precision of 0.01 cm under the worst-case contract and 0.22x at 0.1 cm under the mean contract, decodes on one CPU core, and transfers without retraining to a species absent from training. Project page: https://rubbly.cn/publications/curvecodec/”
Exact source · revision 1Source owner not reported
Reported quantity · bytes: 0.22 other · Basis not reported · Differing source assertions
“odec 2 needs 0.37x ACL's bytes at ACL's default precision of 0.01 cm under the worst-case contract and 0.22x at 0.1 cm under the mean contract, decodes on one CPU core, and transfers without retraining to a species absent from training. Project page: https://rubbly.cn/publications/curvecodec/”
Exact source · revision 1Source owner not reported
Reported quantity · clips: 4472 other · reported trials
“ub-track as a curve in the log map, quantized in closed loop and thinned to rate-distortion-selected keys, with residuals entropy-coded under a small learned model whose integer inference is bit-exact across platforms. Two contracts are verified on every decoded clip: ACL's own worst case per joint within a stated tolerance, or ACL's mean error per clip. On a held-out test side of 4,472 clips from 33 datasets, CurveC”
Exact source · revision 1Source owner not reported
Reported quantity · datasets: 33 other · reported trials
“ub-track as a curve in the log map, quantized in closed loop and thinned to rate-distortion-selected keys, with residuals entropy-coded under a small learned model whose integer inference is bit-exact across platforms. Two contracts are verified on every decoded clip: ACL's own worst case per joint within a stated tolerance, or ACL's mean error per clip. On a held-out test side of 4,472 clips from 33 datasets, CurveC”
Exact source · revision 1Source owner not reported
Reported quantity · percent: 0.01 other · Basis not reported · Differing source assertions
“odec 2 needs 0.37x ACL's bytes at ACL's default precision of 0.01 cm under the worst-case contract and 0.22x at 0.1 cm under the mean contract, decodes on one CPU core, and transfers without retraining to a species absent from training. Project page: https://rubbly.cn/publications/curvecodec/”
Exact source · revision 1Source owner not reported
Reported quantity · percent: 0.1 other · Basis not reported · Differing source assertions
“odec 2 needs 0.37x ACL's bytes at ACL's default precision of 0.01 cm under the worst-case contract and 0.22x at 0.1 cm under the mean contract, decodes on one CPU core, and transfers without retraining to a species absent from training. Project page: https://rubbly.cn/publications/curvecodec/”
Exact source · revision 1Source owner not reported
Reported quantity · core: 1 other · Basis not reported
“odec 2 needs 0.37x ACL's bytes at ACL's default precision of 0.01 cm under the worst-case contract and 0.22x at 0.1 cm under the mean contract, decodes on one CPU core, and transfers without retraining to a species absent from training. Project page: https://rubbly.cn/publications/curvecodec/”
Exact source · revision 1Source owner not reported
Artifact availability · code: reported pending
“odec 2 needs 0.37x ACL's bytes at ACL's default precision of 0.01 cm under the worst-case contract and 0.22x at 0.1 cm under the mean contract, decodes on one CPU core, and transfers without retraining to a species absent from training. Project page: https://rubbly.cn/publications/curvecodec/”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalCurveCodec 2: Skeleton-agnostic animation compression with a learned entropy model
This research paper introduces CurveCodec 2, an animation compression system that achieves significant data reduction for skeletal motion. The method utilizes a learned entropy model to code residuals after quantizing curves in the log map and thinning them based on rate-distortion criteria. On a held-out test set of 4,472 clips from 33 datasets, CurveCodec 2 requires only 0.37x the bytes of the industry-standard ACL library at its default precision (0.01 cm) under a worst-case error contract, while decoding on a single CPU core and transferring without retraining to unseen skeleton types.
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