Papers Image Compression
“Image Compression” 태그가 달린 논문 1,163편 · 필터 해제
LL-GaussianImage: Efficient Image Representation for Zero-shot Low-Light Enhancement with 2D Gaussian Splatting
2D Gaussian Splatting (2DGS) is an emerging explicit scene representation method with significant potential for image compression due to high fidelity and high compression ratios. However, existing low-light enhancement …
Image CompressionGIC-DLC: Differentiable Logic Circuits for Hardware-Friendly Grayscale Image Compression
Neural image codecs achieve higher compression ratios than traditional hand-crafted methods such as PNG or JPEG-XL, but often incur substantial computational overhead, limiting their deployment on energy-constrained devi…
Image CompressionTowards Efficient Low-rate Image Compression with Frequency-aware Diffusion Prior Refinement
Recent advancements in diffusion-based generative priors have enabled visually plausible image compression at extremely low bit rates. However, existing approaches suffer from slow sampling processes and suboptimal bit a…
Image ReconstructionImage CompressionEfficient training for compact compression models via sequential distillation
Deep learning models for image compression often face practical limitations in hardware-constrained applications. Although these models achieve high-quality reconstructions, they are typically complex, heavyweight, and r…
Knowledge DistillationImage CompressionPerformance Analysis of DCT, Hadamard, and PCA in Block-Based Image Compression
Block based image compression relies on transform coding to concentrate signal energy into a small number of coefficients. While classical codecs use fixed transforms such as the Discrete Cosine Transform (DCT), data dri…
Image CompressionYODA: Yet Another One-step Diffusion-based Video Compressor
While one-step diffusion models have recently excelled in perceptual image compression, their application to video remains limited. Prior efforts typically rely on pretrained 2D autoencoders that generate per-frame laten…
Image CompressionSpectral and Spatial Graph Learning for Multispectral Solar Image Compression
High-fidelity compression of multispectral solar imagery remains challenging for space missions, where limited bandwidth must be balanced against preserving fine spectral and spatial details. We present a learned image c…
Image CompressionGraph EmbeddingGraph LearningLongFly: Long-Horizon UAV Vision-and-Language Navigation with Spatiotemporal Context Integration
Unmanned aerial vehicles (UAVs) are crucial tools for post-disaster search and rescue, facing challenges such as high information density, rapid changes in viewpoint, and dynamic structures, especially in long-horizon na…
Image CompressionProgressive Learned Image Compression for Machine Perception
Recent advances in learned image codecs have been extended from human perception toward machine perception. However, progressive image compression with fine granular scalability (FGS)-which enables decoding a single bits…
Image CompressionGenerative Latent Coding for Ultra-Low Bitrate Image Compression
Most existing image compression approaches perform transform coding in the pixel space to reduce its spatial redundancy. However, they encounter difficulties in achieving both high-realism and high-fidelity at low bitrat…
Image CompressionImage RestorationStyle TransferSmartSplat: Feature-Smart Gaussians for Scalable Compression of Ultra-High-Resolution Images
Recent advances in generative AI have accelerated the production of ultra-high-resolution visual content, posing significant challenges for efficient compression and real-time decoding on end-user devices. Inspired by 3D…
Image CompressionSLIM: Semantic-based Low-bitrate Image compression for Machines by leveraging diffusion
In recent years, the demand of image compression models for machine vision has increased dramatically. However, the training frameworks of image compression still focus on the vision of human, maintaining the excessive p…
Image CompressionImage Compression Using Singular Value Decomposition
Images are a substantial portion of the internet, making efficient compression important for reducing storage and bandwidth demands. This study investigates the use of Singular Value Decomposition and low-rank matrix app…
Image CompressionTreeNet: A Light Weight Model for Low Bitrate Image Compression
Reducing computational complexity remains a critical challenge for the widespread adoption of learning-based image compression techniques. In this work, we propose TreeNet, a novel low-complexity image compression model …
Image CompressionGenerative Preprocessing for Image Compression with Pre-trained Diffusion Models
Preprocessing is a well-established technique for optimizing compression, yet existing methods are predominantly Rate-Distortion (R-D) optimized and constrained by pixel-level fidelity. This work pioneers a shift towards…
parameter-efficient fine-tuningImage CompressionVLIC: Vision-Language Models As Perceptual Judges for Human-Aligned Image Compression
Evaluations of image compression performance which include human preferences have generally found that naive distortion functions such as MSE are insufficiently aligned to human perception. In order to align compression …
Image CompressionVisual ReasoningUltra-Low Bitrate Perceptual Image Compression with Shallow Encoder
Ultra-low bitrate image compression (below 0.05 bits per pixel) is increasingly critical for bandwidth-constrained and computation-limited encoding scenarios such as edge devices. Existing frameworks typically rely on la…
Image CompressionEmbodied Image Compression
Image Compression for Machines (ICM) has emerged as a pivotal research direction in the field of visual data compression. However, with the rapid evolution of machine intelligence, the target of compression has shifted f…
Image CompressionROI-Packing: Efficient Region-Based Compression for Machine Vision
This paper introduces ROI-Packing, an efficient image compression method tailored specifically for machine vision. By prioritizing regions of interest (ROI) critical to end-task accuracy and packing them efficiently whil…
Instance SegmentationImage CompressionObject DetectionPersistent Homology-Guided Frequency Filtering for Image Compression
Feature extraction in noisy image datasets presents many challenges in model reliability. In this paper, we use the discrete Fourier transform in conjunction with persistent homology analysis to extract specific frequenc…
Binary ClassificationImage Compression