pith:OJKE2CHN
TVRN: Invertible Neural Networks for Compression-Aware Temporal Video Rescaling
TVRN's invertible architecture and surrogate network enable end-to-end compression-aware video frame rate rescaling.
arxiv:2605.15579 v1 · 2026-05-15 · eess.IV · cs.CV
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Claims
Extensive experiments show that TVRN outperforms existing methods in reconstruction quality under industrial video compression settings.
The surrogate network provides sufficiently accurate gradient approximations for non-differentiable lossy codecs so that end-to-end optimization remains stable and does not introduce artifacts that would not appear with the true codec.
TVRN combines invertible wavelet-based networks with a surrogate gradient approximator and compression-aware asymmetric design to improve frame-rate rescaling quality under real codecs.
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Receipt and verification
| First computed | 2026-05-20T00:01:06.438462Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/OJKE2CHNLEFZ6SDWBTNMDWCWPK \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 72544d08ed590b9f48760cdac1d8567ab1835caba146e6ea2c752d8ecd68acf4
Canonical record JSON
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