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hgpu.org » Applications » Computer science » Computer vision

A GPU-based Affine and Scale Invariant Feature Transform Algorithm

Guofeng Tong, Xiangnan Meng, Ning Ye

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Tags: Algorithms, Computer science, Computer vision, CUDA, Interactive application, nVidia, nVidia GeForce GTX 560 Ti

September 14, 2013 by hgpu

GPU Implementations of Object Detection using HOG Features and Deformable Models

Manato Hirabayashi, Shinpei Kato, Masato Edahiro, Kazuya Takeda, Taiki Kawano, Seiichi Mita

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Tesla K20

September 11, 2013 by hgpu

Fast Object Re-Detection and Localization in Video for Spatio-Temporal Fragment Creation

Evlampios Apostolidis, Vasileios Mezaris, Ioannis Kompatsiaris

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Tags: Algorithms, Computer science, Computer vision, nVidia, nVidia GeForce GTX 560, OpenCV

August 26, 2013 by hgpu

Performance Optimization of Vision Apps on Mobile Application Processor

Kwang-Ting (Tim) Cheng, Xin Yang and Yi-Chu Wang

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Tags: Computer science, Computer vision, Heterogeneous systems, nVidia, nVidia Tegra, OpenGL

August 24, 2013 by hgpu

A Unified Framework for Multi-Sensor HDR Video Reconstruction

Joel Kronander, Stefan Gustavson, Gerhard Bonnet, Anders Ynnerman, Jonas Unger

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 680

August 23, 2013 by hgpu

Accelerating Random Forests on CPUs and GPUs for Object-Class Image Segmentation

Benedikt Waldvogel

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Tags: Computer science, Computer vision, CUDA, Machine learning, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, Package, Tesla K20, Thesis

August 16, 2013 by hgpu

An Automated Video Surveillance System Using Viewpoint Feature Histogram and CUDA-enabled GPUs

Saurabh Jha, Priyank Trivedi

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Tags: Computer science, Computer vision, CUDA, nVidia, Tesla M2050

August 14, 2013 by hgpu

Heterogeneous Computing for Real-Time Stereo Matching

A. AL-Marakeby, M. Zaki

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 610 M, Stereo vision

August 10, 2013 by hgpu

Real-time 3D semi-local surface patch extraction using GPGPU

Sergio Orts-Escolano, Vicente Morell, Jose Garcia-Rodriguez, Miguel Cazorla, Robert B. Fisher

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GT 630 M, nVidia GeForce GTX 480

July 29, 2013 by hgpu

Detecting parametric objects in large scenes by Monte Carlo sampling

Yannick Verdie, Florent Lafarge

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia Quadro FX 4800

July 21, 2013 by hgpu

Parallel Image Segmentation Using Reduction-Sweeps On Multicore Processors and GPUs

Renato Farias, Ricardo Farias, Ricardo Marroquim, Esteban Clua

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Tags: Algorithms, Clustering, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 470

July 19, 2013 by hgpu

Fast PCA-BAsed Face Recognition on GPUs

Youngsang Woo, Cheongyong Yi, Youngmin Yi

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Tags: Algorithms, Biometrics, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 580

July 12, 2013 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

A GPU-based Affine and Scale Invariant Feature Transform Algorithm

GPU Implementations of Object Detection using HOG Features and Deformable Models

Fast Object Re-Detection and Localization in Video for Spatio-Temporal Fragment Creation

Performance Optimization of Vision Apps on Mobile Application Processor

A Unified Framework for Multi-Sensor HDR Video Reconstruction

Accelerating Random Forests on CPUs and GPUs for Object-Class Image Segmentation

An Automated Video Surveillance System Using Viewpoint Feature Histogram and CUDA-enabled GPUs

Heterogeneous Computing for Real-Time Stereo Matching

Real-time 3D semi-local surface patch extraction using GPGPU

Detecting parametric objects in large scenes by Monte Carlo sampling

Parallel Image Segmentation Using Reduction-Sweeps On Multicore Processors and GPUs

Fast PCA-BAsed Face Recognition on GPUs

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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