high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer vision

SINGA: Putting Deep Learning in the Hands of Multimedia Users

Wei Wang, Gang Chen, Tien Tuan Anh Dinh, Jinyang Gao, Beng Chin Ooi, Kian-Lee Tan, Sheng Wang

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, Deep learning, Distributed computing, Package

August 11, 2015 by hgpu

Places205-VGGNet Models for Scene Recognition

Limin Wang, Sheng Guo, Weilin Huang, Yu Qiao

View

Download (PDF)

Source codes

Tags: Caffe, Computer science, Computer vision, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package

August 10, 2015 by hgpu

DenseCut: Densely Connected CRFs for Realtime GrabCut

M. M. Cheng, V. A. Prisacariu, S. Zheng, P. H. S. Torr, C. Rother

View

Download (PDF)

Source codes

Tags: Computer vision, CUDA, Image processing, nVidia, Package, Tesla K40

August 7, 2015 by hgpu

Towards Distortion-Predictable Embedding of Neural Networks

Axel Angel

View

Download (PDF)

Source codes

Tags: Caffe, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Package, Thesis

August 7, 2015 by hgpu

Real-Time Pedestrian Detection With Deep Networks Cascades

Anelia Angelova, Alex Krizhevsky, Vincent Vanhoucke, Abhijit Ogale, Dave Ferguson

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla K20

August 6, 2015 by hgpu

Target Marker: A Visual Marker for Long Distances and Detection in Realtime on Mobile Devices

Oliver Christen, Edwin Naroska, Alexander Micheel, Shanq-Jang Ruan

View

Download (PDF)

Tags: Computer science, Computer vision, Image recognition, OpenCL, OpenCV

August 5, 2015 by hgpu

Semantic Pose using Deep Networks Trained on Synthetic RGB-D

Jeremie Papon, Markus Schoeler

View

Download (PDF)

Tags: CNN, Computer science, Computer vision, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, Rendering

August 5, 2015 by hgpu

Face Search at Scale: 80 Million Gallery

Dayong Wang, Charles Otto, Anil K. Jain

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Deep learning, Face detection, nVidia

August 3, 2015 by hgpu

Real-Time Scheduling for GPUs with Applications in Advanced Automotive Systems

Glenn A. Elliott

View

Download (PDF)

Tags: Computer science, Computer vision, nVidia, nVidia Quadro K5000, Task scheduling, Thesis

August 3, 2015 by hgpu

Experiences in Speeding Up Computer Vision Applications on Mobile Computing Platforms

Luna Backes, Alejandro Rico, Bjorn Franke

View

Download (PDF)

Tags: ARM, Computer science, Computer vision, Embedded high-performance computing, OpenCL

July 28, 2015 by hgpu

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Baoguang Shi, Xiang Bai, Cong Yao

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Tesla K40

July 24, 2015 by hgpu

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

Keiron O'Shea

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 580

July 24, 2015 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

SINGA: Putting Deep Learning in the Hands of Multimedia Users

Places205-VGGNet Models for Scene Recognition

DenseCut: Densely Connected CRFs for Realtime GrabCut

Towards Distortion-Predictable Embedding of Neural Networks

Real-Time Pedestrian Detection With Deep Networks Cascades

Target Marker: A Visual Marker for Long Distances and Detection in Realtime on Mobile Devices

Semantic Pose using Deep Networks Trained on Synthetic RGB-D

Face Search at Scale: 80 Million Gallery

Real-Time Scheduling for GPUs with Applications in Advanced Automotive Systems

Experiences in Speeding Up Computer Vision Applications on Mobile Computing Platforms

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Most viewed papers (last 30 days)