Compressed look-up-table based real-time rectification hardware

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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 ...

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 ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

Cross-resolution face recognition has become a challenging problem for modern deep face recognition systems. It aims at matching a low-resolution probe image with high-resolution gallery images registered in a database. Existing methods mainly leverage pri ...

Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from keypoint correspondences established between monocular 2D images. Current NRSfM methods lack statistical robustness, which is the ability to cope with correspondence errors. T ...

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 ...

Model compression techniques have lead to a reduction of size and number of computations of Deep Learning models. However, techniques such as pruning mostly lack of a real co-optimization with hardware platforms. For instance, implementing unstructured pru ...

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

Scene and reference results files for: "A Critical Comparison of Annual Glare Simulation Methods" Stephen Wasilewski, Jan Wienold, Marilyne Andersen 2022 Buildsim Nordic, Copenhagen Contents: 01-06*.tar.gz: reference simulation image archives, one ...

Human visual system relies on both monocular focusness cues and binocular stereo cues to gain effective 3D perception. Correspondingly, depth from focus/defocus (DfF/DfD) and stereo matching are two most studied passive depth sensing schemes, which are tra ...

An innovative photogrammetric pipeline has been developed by INAF-Padova for the processing of the stereo images from the CaSSIS (Colour and Stereo Imaging System) (Thomas et al., 2014). CaSSIS is the multispectral stereo push frame camera on board ExoMars ...

Monocular and stereo visions are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots. However, they are usually developed independently and have their respective strengths and limitations. We propose a no ...

Human-centered scene understanding is the process of perceiving and analysing a dynamic scene observed through a network of sensors with emphasis on human-related activities. It includes the visual perception of human-related activities from either single ...

The human face plays an essential role in social interactions as it brings information about someone's identity, state of mind, or mood. People are, by nature, very good at catching this non-spoken information. Therefore, scientists have been interested in ...

Even if Dennard scaling came to an end fifteen years ago, Moore' s law kept fueling an exponential growth in compute performance through increased parallelization. However, the performance of memory and, in particular, Dynamic Random Access Memory (DRAM), ...

We address the detection, tracking, and relative localization of the agents of a drone swarm from a human perspective using a headset equipped with a single camera and an Inertial Measurement Unit (IMU). We train and deploy a deep neural network detector o ...

The cameras are invented by imitating the human visual system to capture the scene. The camera technologies have been substantially advanced in recent years. 108 MP resolution with 100x hybrid zoom has become standard features for smartphone flagships. In ...

Autofocus (AF) methods are extensively used in biomicroscopy, for example to acquire timelapses, where the imaged objects tend to drift out of focus. AF algorithms determine an optimal distance by which to move the sample back into the focal plane. Current ...

Stereo reconstruction is a problem of recovering a 3d structure of a scene from a pair of images of the scene, acquired from different viewpoints. It has been investigated for decades and many successful methods were developed. The main drawback of these ...

Stereo matching aims to perceive the 3D geometric configuration of scenes and facilitates a variety of computer vision in advanced driver assistance systems (ADAS) applications. Recently, deep convolutional neural networks (CNNs) have shown dramatic perfor ...

Compressed look-up-table based real-time rectification hardware

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Aggregating Spatial and Photometric Context for Photometric Stereo

Neural Distributed Image Compression with Cross-Attention Feature Alignment

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

Robust Isometric Non-Rigid Structure-From-Motion

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

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations

Attribute Prediction as Multiple Instance Learning

reference data for "A Critical Comparison of Annual Glare Simulation Methods"

Deep eyes: Joint depth inference using monocular and binocular cues

3DPD: A photogrammetric pipeline for a PUSH frame stereo cameras

MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization

Human-Centered Scene Understanding via Crowd Counting

Model-based 3D Face Reconstruction

Miss-Optimized Memory Systems: Turning Thousands of Outstanding Misses into Reuse Opportunities

Tracking and Relative Localization of Drone Swarms With a Vision-Based Headset

Beyond Cameras: Real-Time High-Resolution 3D and Panoramic MultiView Vision Systems with Their Applications

DeepFocus: a Few-shot Microscope Slide Auto-Focus using a Sample Invariant CNN-based Sharpness Function

Learning stereo reconstruction with deep neural networks

Unsupervised Stereo Matching Using Confidential Correspondence Consistency