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Found 10 papers, 3 papers with code
Compressible and Searchable: AI-native Multi-Modal Retrieval System with Learned Image Compression
The burgeoning volume of digital content across diverse modalities necessitates efficient storage and retrieval methods.
Task-Aware Encoder Control for Deep Video Compression
Prior research on deep video compression (DVC) for machine tasks typically necessitates training a unique codec for each specific task, mandating a dedicated decoder per task.
Super-High-Fidelity Image Compression via Hierarchical-ROI and Adaptive Quantization
MSE-based models aim to improve objective metrics while generative models are leveraged to improve visual quality measured by subjective metrics.
Unified learning-based lossy and lossless JPEG recompression
Most image compression algorithms only consider uncompressed original image, while ignoring a large number of already existing JPEG images.
Efficient Learned Lossless JPEG Recompression
Second, we propose pipeline parallel context model (PPCM) and compressed checkerboard context model (CCCM) for the effective conditional modeling and efficient decoding within luma and chroma components.
Learned Lossless Compression for JPEG via Frequency-Domain Prediction
In this paper, we propose a novel framework for learned lossless compression of JPEG images that achieves end-to-end optimized prediction of the distribution of decoded DCT coefficients.
Bit Allocation using Optimization
In this paper, we consider the problem of bit allocation in Neural Video Compression (NVC).
Evaluating the Practicality of Learned Image Compression
On CPU, the latency of our implementation is comparable with JPEG XL.
PO-ELIC: Perception-Oriented Efficient Learned Image Coding
In the past years, learned image compression (LIC) has achieved remarkable performance.
GCN-MIF: Graph Convolutional Network with Multi-Information Fusion for Low-dose CT Denoising
To address this issue, we propose a novel graph convolutional network-based LDCT denoising model, namely GCN-MIF, to explicitly perform multi-information fusion for denoising purpose.
