Papers Image Compression
“Image Compression” 태그가 달린 논문 1,163편 · 필터 해제
CMamba: Learned Image Compression with State Space Models
Learned Image Compression (LIC) has explored various architectures, such as Convolutional Neural Networks (CNNs) and transformers, in modeling image content distributions in order to achieve compression effectiveness. Ho…
Image CompressionState Space ModelsAll-in-One Image Compression and Restoration
Visual images corrupted by various types and levels of degradations are commonly encountered in practical image compression. However, most existing image compression methods are tailored for clean images, therefore strug…
AllImage CompressionImage RestorationCompressed Image Generation with Denoising Diffusion Codebook Models
We present a novel generative approach based on Denoising Diffusion Models (DDMs), which produces high-quality image samples along with their losslessly compressed bit-stream representations. This is obtained by replacin…
Conditional Image GenerationDenoisingDiversityImage Compression+2S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression
Transformer-based Learned Image Compression (LIC) suffers from a suboptimal trade-off between decoding latency and rate-distortion (R-D) performance. Moreover, the critical role of the FeedForward Network (FFN)-based cha…
Image CompressionSemantic Communication based on Generative AI: A New Approach to Image Compression and Edge Optimization
As digital technologies advance, communication networks face challenges in handling the vast data generated by intelligent devices. Autonomous vehicles, smart sensors, and IoT systems necessitate new paradigms. This thes…
Autonomous VehiclesComputational EfficiencyDenoisingImage Compression+2On Disentangled Training for Nonlinear Transform in Learned Image Compression
Learned image compression (LIC) has demonstrated superior rate-distortion (R-D) performance compared to traditional codecs, but is challenged by training inefficiency that could incur more than two weeks to train a state…
Image CompressionDiffusion-based Perceptual Neural Video Compression with Temporal Diffusion Information Reuse
Recently, foundational diffusion models have attracted considerable attention in image compression tasks, whereas their application to video compression remains largely unexplored. In this article, we introduce DiffVC, a…
Image CompressionQuantizationVideo CompressionTowards Loss-Resilient Image Coding for Unstable Satellite Networks
Geostationary Earth Orbit (GEO) satellite communication demonstrates significant advantages in emergency short burst data services. However, unstable satellite networks, particularly those with frequent packet loss, pres…
DecoderImage CompressionEmergence of Painting Ability via Recognition-Driven Evolution
From Paleolithic cave paintings to Impressionism, human painting has evolved to depict increasingly complex and detailed scenes, conveying more nuanced messages. This paper attempts to emerge this artistic capability by …
Image CompressionUnified Coding for Both Human Perception and Generalized Machine Analytics with CLIP Supervision
The image compression model has long struggled with adaptability and generalization, as the decoded bitstream typically serves only human or machine needs and fails to preserve information for unseen visual tasks. Theref…
Image CompressionAn Efficient Adaptive Compression Method for Human Perception and Machine Vision Tasks
While most existing neural image compression (NIC) and neural video compression (NVC) methodologies have achieved remarkable success, their optimization is primarily focused on human visual perception. However, with the …
Image CompressionVideo CompressionRegion of Interest based Medical Image Compression
The vast volume of medical image data necessitates efficient compression techniques to support remote healthcare services. This paper explores Region of Interest (ROI) coding to address the balance between compression ra…
DiagnosticImage CompressionUNET SegmentationTest-Time Fine-Tuning of Image Compression Models for Multi-Task Adaptability
The field of computer vision was initially inspired by the human visual system and has progressively expanded to include a broader range of machine vision applications. Consequently, image compressors should be desig…
Image CompressionDecouple Distortion from Perception: Region Adaptive Diffusion for Extreme-low Bitrate Perception Image Compression
Leveraging the generative power of diffusion models, generative image compression has achieved impressive perceptual fidelity even at extremely low bitrates. However, current methods often neglect the non-uniform com…
DecoderImage CompressionLocal DistortionFrequency-Biased Synergistic Design for Image Compression and Compensation
Compression artifacts removal (CAR), an effective post-processing method to reduce compression distortion in edge-side codecs, demonstrates remarkable results by utilizing convolutional neural networks (CNNs) on high…
Image CompressionQuantizationMultirate Neural Image Compression with Adaptive Lattice Vector Quantization
Recent research has explored integrating lattice vector quantization (LVQ) into learned image compression models. Due to its more efficient Voronoi covering of vector space than scalar quantization (SQ), LVQ achieves…
Domain AdaptationImage CompressionQuantizationFitted Neural Lossless Image Compression
Neural lossless image compression methods have recently achieved impressive compression ratios by fitting neural networks to represent data distributions of large datasets. However, these methods often require comple…
Image CompressionUltra-Low Complexity On-Orbit Compression for Remote Sensing Imagery via Block Modulated Imaging
The growing field of remote sensing faces a challenge: the ever-increasing size and volume of imagery data are exceeding the storage and transmission capabilities of satellite platforms. Efficient compression of remote s…
compressed sensingImage CompressionSemantics Disentanglement and Composition for Versatile Codec toward both Human-eye Perception and Machine Vision Task
While learned image compression methods have achieved impressive results in either human visual perception or machine vision tasks, they are often specialized only for one domain. This drawback limits their versatility a…
DisentanglementImage CompressionMERCURY: A fast and versatile multi-resolution based global emulator of compound climate hazards
High-impact climate damages are often driven by compounding climate conditions. For example, elevated heat stress conditions can arise from a combination of high humidity and temperature. To explore future changes in com…
Image Compression