ActDiff-VC achieves up to 64.6% bitrate reduction at matched NIQE and improves perceptual metrics like KID and FID by using content-adaptive keyframe selection and budget-aware sparse trajectory selection to condition a diffusion decoder for ultra-low-bitrate video reconstruction.
End-to-end optimized image compression
9 Pith papers cite this work. Polarity classification is still indexing.
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representative citing papers
GS-SCNet unifies 3D Gaussian Splatting with a disparity-guided semantic codec and direct Gaussian parameter prediction for efficient real-time 3D video communications with strong generalization.
SAD is a new explicit differentiable image representation based on soft anisotropic additively weighted Voronoi partitions that achieves higher PSNR and 4-19x faster training than Image-GS and Instant-NGP at matched bitrate.
NDGI compresses temporal lightmaps via neural feature maps and lightweight networks, delivering high-quality dynamic global illumination with low storage and modest real-time decompression cost.
Finite scalar quantization simplifies VQ-VAE latents by independently rounding a few dimensions to fixed levels, producing an equivalent-sized implicit codebook with competitive performance and no collapse.
RDVQ enables joint rate-distortion optimization for vector-quantized generative image compression via differentiable codebook distribution relaxation and an autoregressive entropy model.
A practical learned image codec delivers 2.3-3x bitrate savings over AV1/VVC and 20-40% over prior learned codecs while encoding 12MP images in 230ms on iPhone.
SAMIC introduces semantic-aware Mamba blocks and SVD-based redundancy reduction to achieve efficient perceptual image compression with improved rate-distortion-perception tradeoffs.
A bilinear CNN that fuses features from a distortion-type classifier and an image classifier achieves superior BIQA performance on both synthetic and authentic distortion databases.
citing papers explorer
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Active Sampling for Ultra-Low-Bit-Rate Video Compression via Conditional Controlled Diffusion
ActDiff-VC achieves up to 64.6% bitrate reduction at matched NIQE and improves perceptual metrics like KID and FID by using content-adaptive keyframe selection and budget-aware sparse trajectory selection to condition a diffusion decoder for ultra-low-bitrate video reconstruction.
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Generalizable 3D Gaussian Splatting enabled Semantic Coding for Real-Time Immersive Video Communications
GS-SCNet unifies 3D Gaussian Splatting with a disparity-guided semantic codec and direct Gaussian parameter prediction for efficient real-time 3D video communications with strong generalization.
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Soft Anisotropic Diagrams for Differentiable Image Representation
SAD is a new explicit differentiable image representation based on soft anisotropic additively weighted Voronoi partitions that achieves higher PSNR and 4-19x faster training than Image-GS and Instant-NGP at matched bitrate.
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Neural Dynamic GI: Random-Access Neural Compression for Temporal Lightmaps in Dynamic Lighting Environments
NDGI compresses temporal lightmaps via neural feature maps and lightweight networks, delivering high-quality dynamic global illumination with low storage and modest real-time decompression cost.
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Finite Scalar Quantization: VQ-VAE Made Simple
Finite scalar quantization simplifies VQ-VAE latents by independently rounding a few dimensions to fixed levels, producing an equivalent-sized implicit codebook with competitive performance and no collapse.
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Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression
RDVQ enables joint rate-distortion optimization for vector-quantized generative image compression via differentiable codebook distribution relaxation and an autoregressive entropy model.
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What Matters in Practical Learned Image Compression
A practical learned image codec delivers 2.3-3x bitrate savings over AV1/VVC and 20-40% over prior learned codecs while encoding 12MP images in 230ms on iPhone.
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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.
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Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
A bilinear CNN that fuses features from a distortion-type classifier and an image classifier achieves superior BIQA performance on both synthetic and authentic distortion databases.