high performance computing on graphics processing units: hgpu.org

hgpu.org » Optical flow

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

A self-organization based optical flow estimator with GPU implementation

Manish Shiralkar, Robert Schalkoff

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

PROST: Parallel robust online simple tracking

Jakob Santner, Christian Leistner, Amir Saffari, Thomas Pock, Horst Bischof

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Tags: Computer science, Computer vision, nVidia, Optical flow, Video tracking

July 19, 2011 by hgpu

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

Experiences in Building a Composable and Functional API for Runtime SPIR-V Code Generation

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

TorchBench: Benchmarking PyTorch with High API Surface Coverage

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Descend: A Safe GPU Systems Programming Language

Redwood heterogeneous framework

Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads

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high performance computing on graphics processing units: hgpu.org

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)

A self-organization based optical flow estimator with GPU implementation

PROST: Parallel robust online simple tracking

Recent source codes

Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis

AutoDock for GPUs and other accelerators

spotPython: Sequential Parameter Optimization in Python

Test benchmarks for CELERITY

Dragon-Alpha&cu32: A Java-based Tensor Computing Framework With its High-Performance CUDA Library

Beehive SPIR-V Toolkit

TorchBench: a collection of open source benchmarks used to evaluate PyTorch performance

Prediction of Performance and Power Consumption of GPGPU Applications

Descend: an attempt at safe imperative GPU programming

Redwood heterogeneous framework

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