high performance computing on graphics processing units: hgpu.org

hgpu.org » Optical flow

Compute-unified device architecture implementation of a block-matching algorithm for multiple graphical processing unit cards

Francesc Massanes, Marie Cadennes, Jovan G. Brankov

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Tags: Algorithms, Computational Complexity, CUDA, H.264/AVC, Image processing, nVidia, Optical flow, Tesla C1060, Tesla C2070

November 28, 2011 by hgpu

A low-cost 3D human interface device using GPU-based optical flow algorithms

Rafael del Riego, Jose Otero, Jose Ranilla

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Tags: Algorithms, CAD, Computer science, nVidia, nVidia GeForce 9500 GT, nVidia GeForce 9500 M, Optical flow

November 27, 2011 by hgpu

GPU-based Signal Processing Scheme for Bioinspired Optical Flow

Fermin Ayuso, Carlos Garcia, Guillermo Botella, Manuel Prieto, Francisco Tirado

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Tags: CUDA, Filtering, nVidia, Optical flow, Signal processing, Tesla C1060

November 8, 2011 by hgpu

Fast TV-L1 Optical Flow for Interactivity

Emmanuel d'Angelo, Johan Paratte, Gilles Puy, Pierre Vandergheynst

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Tags: Algorithms, Computer science, Computer vision, nVidia, nVidia GeForce GTX 320 M, OpenCL, Optical flow, Optimization, Package

November 7, 2011 by hgpu

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Robert Hegner

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package, Thesis

October 27, 2011 by hgpu

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

Robert Hegner, Ivar Austvoll, Tom Ryen, Guido M. Schuster

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package

October 27, 2011 by hgpu

General purpose computing on graphics processing units using OpenCL

Mats Johansson, Oscar Winter

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Tags: Algorithms, ATI, ATI Radeon HD 4870, ATI Stream, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 480, OpenCL, Optical flow, Optimization, Thesis

October 12, 2011 by hgpu

A parallel mapping of optical flow to Compute Unified Device Architecture for motion-based image segmentation

Peter Kuchnio, David W. Capson

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 280, Optical flow

August 10, 2011 by hgpu

A pure vision-based approach to topological SLAM

Wen Lik Dennis Lui, Ray Jarvis

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Optical flow, Wavelet

August 7, 2011 by hgpu

Polyconvexification of the multi-label optical flow problem

N. Papadakis, A. Baeza, P. Gargallo, V. Caselles

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Tags: Algorithms, Computer science, CUDA, nVidia, Optical flow

August 6, 2011 by hgpu

Adaptive, real-time visual simultaneous localization and mapping

Brian Clipp, Christopher Zach, Jongwoo Lim, Jan-Michael Frahm, Marc Pollefeys

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Tags: Computer science, Computer vision, CUDA, nVidia, Optical flow, Optimization, SIFT, Video tracking

August 1, 2011 by hgpu

A self-organization based optical flow estimator with GPU implementation (thesis)

Manish Shiralkar

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480, nVidia Quadro FX 5600, nVidia Quadro NVS 140 M, Optical flow, Self-organizing map, Tesla T10, Thesis

July 22, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Compute-unified device architecture implementation of a block-matching algorithm for multiple graphical processing unit cards

A low-cost 3D human interface device using GPU-based optical flow algorithms

GPU-based Signal Processing Scheme for Bioinspired Optical Flow

Fast TV-L1 Optical Flow for Interactivity

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

General purpose computing on graphics processing units using OpenCL

A parallel mapping of optical flow to Compute Unified Device Architecture for motion-based image segmentation

A pure vision-based approach to topological SLAM

Polyconvexification of the multi-label optical flow problem

Adaptive, real-time visual simultaneous localization and mapping

A self-organization based optical flow estimator with GPU implementation (thesis)

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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