Towards a Comprehensive RVC VTL: A CAL Description of an Efficient AVC Baseline Encoder

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Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...

Due to its high parallelism, belief propagation (BP)decoding is amenable to high-throughput applications and thusrepresents a promising solution for the ultra-high peak datarate required by future communication systems. To bridge theperformance gap compare ...

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

Visual data play a crucial role in modern society, and the rate at which images and videos are acquired, stored, and exchanged every day is rapidly increasing. Image compression is the key technology that enables storing and sharing of visual content in an ...

In the field of image acquisition, Dynamic Vision Sensors (DVS) present an innovative methodology, capturing only the variations in pixel brightness instead of absolute values and thereby revealing unique features. Given that the primary deployment of DVS ...

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

In 1970, Furth and Yoshikawa (1970 Phys. Fluids 13 2593-6) introduced the scalings of adiabatic plasma compression. Basically, if the shape of the external plasma boundary and the aspect ratio are preserved during the compression, then the density, kinetic ...

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

We consider the problem of compressing an information source when a correlated one is available as side information only at the decoder side, which is a special case of the distributed source coding problem in information theory. In particular, we consider ...

The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...

Modern media data such as 360 degrees videos and light field (LF) images are typically captured in much higher dimensions than the observers' visual displays. To efficiently browse high-dimensional media, a navigational streaming model is considered: a cli ...

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

State-of-the-art 2D image compression schemes rely on the power of convolutional neural networks (CNNs). Although CNNs offer promising perspectives for 2D image compression, extending such models to omnidirectional images is not straightforward. First, omn ...

Towards a Comprehensive RVC VTL: A CAL Description of an Efficient AVC Baseline Encoder

Chattez avec Graph Search

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

High-Throughput and Flexible Belief Propagation List Decoder for Polar Codes

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evaluating the effect of sparse convolutions on point cloud compression

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Shafranov shift correction to the Furth-Yoshikawa scaling of tokamak adiabatic compression

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Neural Distributed Image Compression with Cross-Attention Feature Alignment

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

Landmarking for Navigational Streaming of Stored High-Dimensional Media

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

OSLO: On-the-Sphere Learning for Omnidirectional Images and Its Application to 360-Degree Image Compression