DCIC uses dual constraints on a diffusion decoder to realize adjustable RDP operating points in neural image compression without extra rate cost.
Entroformer: A transformer-based entropy model for learned image compression
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4representative citing papers
ECC integrates hyperprior side information, channel-wise context, latent residual prediction, temporal modeling, and entropy skip into a learned entropy model, yielding 39.9% and 76.3% average BD-rate reductions on ViSQOL and PESQ over baselines.
A spatial hyperprior compressed by MED plus a tiny learned context model conditions Cool-Chic-style entropy models and yields 1.4–3% BD-rate gains at 606–1481 MAC/pixel.
SAMIC introduces semantic-aware Mamba blocks and SVD-based redundancy reduction to achieve efficient perceptual image compression with improved rate-distortion-perception tradeoffs.
citing papers explorer
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Dual-Constrained Diffusion Image Compression for Operational Rate-Distortion-Perception Optimization
DCIC uses dual constraints on a diffusion decoder to realize adjustable RDP operating points in neural image compression without extra rate cost.
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Benchmarking Neural Speech Compression from a Rate-Distortion Perspective
ECC integrates hyperprior side information, channel-wise context, latent residual prediction, temporal modeling, and entropy skip into a learned entropy model, yielding 39.9% and 76.3% average BD-rate reductions on ViSQOL and PESQ over baselines.
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LANCE: Locally Adaptive Neural Context Estimation for Overfitted Image Compression
A spatial hyperprior compressed by MED plus a tiny learned context model conditions Cool-Chic-style entropy models and yields 1.4–3% BD-rate gains at 606–1481 MAC/pixel.
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SAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression
SAMIC introduces semantic-aware Mamba blocks and SVD-based redundancy reduction to achieve efficient perceptual image compression with improved rate-distortion-perception tradeoffs.