Optical Flow Modeling and Computation: A Survey

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Illuminating resource presenting commonly used robotic methodologies and technologies, with recent developments and clear application examples across different project types Infrastructure Robotics presents state-of-the-art research in infrastructure robot ...

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

Single-photon avalanche diodes (SPADs) are novel image sensors that record the arrival of individual photons at extremely high temporal resolution. In the past, they were only available as single pixels or small-format arrays, for various active imaging ap ...

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since-without additional prior assumpti ...

There are various possibilities to realize coil winding designs for an inductive power transfer system. In order to achieve high power transfer efficiency and power density and explore trade-offs between the two, design optimization around the coil link is ...

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

The transition towards a human-centered indoor climate is beneficial from occupants’ thermal comfort and from an energy reduction perspective. However, achieving this goal requires the knowledge of the thermal state of individuals at the level of body part ...

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...

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 ...

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

This paper introduces TACOSS a text-image alignment approach that allows explainable land cover semantic segmentation by directly integrating semantic concepts encoded from texts. TACOSS combines convolutional neural networks for visual feature extraction ...

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

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 ...

We propose a pre-training strategy called Multi-modal Multi-task Masked Autoencoders (MultiMAE). It differs from standard Masked Autoencoding in two key aspects: I) it can optionally accept additional modalities of information in the input besides the RGB ...

Large training datasets have played a vital role in the success of modern deep learning methods in computer vision. But, obtaining sufficient amount of training data is challenging, specially when annotating volumetric images. This is because fully annotat ...

Advances in scanning systems have enabled the digitization of pathology slides into Whole-Slide Images (WSIs), opening up opportunities to develop Computational Pathology (CompPath) methods for computer-aided cancer diagnosis and prognosis. CompPath has be ...

Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...

During the Artificial Intelligence (AI) revolution of the past decades, deep neural networks have been widely used and have achieved tremendous success in visual recognition. Unfortunately, deploying deep models is challenging because of their huge model s ...

Optical Flow Modeling and Computation: A Survey

Chat with Graph Search

Aggregating Spatial and Photometric Context for Photometric Stereo

Infrastructure Robotics: Methodologies, Robotic Systems and Applications

Automated Human Motion Analysis and Synthesis

Burst Vision Using Single-Photon Cameras

State of the Art in Dense Monocular Non-Rigid 3D Reconstruction

Modeling and Design Optimization of Loosely Coupled PCB Spiral Coils in Inductive Power Transfer Systems

Detecting Anomalies and Obstacles in Road Scenes

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

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

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Text as a Richer Source of Supervision in Semantic Segmentation Tasks

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

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

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Object Priors for Volumetric Image Segmentation

Graph Representation Learning in Computational Pathology

Encoder-Decoder Models for Human Segmentation and Motion Analysis

Improving the Training of Compact Neural Networks for Visual Recognition