The code for Patch-CKN, along with the dataset introduced in the paper, is available here.
The code for EpicFlow (CVPR'15) is available here.
The detection code for "Learning to Detection Motion Boundaries" (CVPR'15) is available here.
Spatio-temporal object detection proposals
The code for Spatio-temporal object detection proposals
(ECCV'14) and the refined spatio-temporal annotations of UCF Sport are available here.
Convolutional Kernel Networks
The code for our NIPS'14 paper on convolutional kernel networks is available on the project web page.
Kernel Temporal Segmentation
The code for "Category-specific video summarization" (ECCV'14) is available here.
The code for our CVPR'14 paper on transformation selection is available on its project page .
The open-source sparse estimation toolbox SPAMS v2.5 has been released. It contains the code for the CVPR'14 paper on archetypal analysis, and the ICML'13 and NIPS'13 papers on large-scale optimization.
Human Pose Estimation in Videos
The code for our CVPR'14 paper Mixing Body-Part Sequences for Human Pose Estimation, is available on the project page.
Segmentation Driven Object Detection with Fisher Vectors
The code for the ICCV'13 paper Segmentation Driven Object Detection with Fisher Vectors by R. Gokberk Cinbis et al. is available here: MaskFishDet.
The code for our Bioinformatics paper on fast RNA-seq isoform deconvolution is available on the project web page and also as a Bioconductor R package.
Code for DeepFlow, an optical flow estimation algorithm based on DeepMatching (see below) and published in our ICCV'13 paper
, is available here
Code for DeepMatching, a dense and robust matching algorithm mentioned in our ICCV'13 paper
, is available here
Improved Trajectories Video Description
The code for improved trajectories in our ICCV'13 paper - can be found on the website of Heng Wang.
Fisher kernels of non-iid image models
The code for our CVPR'12 paper Image categorization using Fisher kernels of non-iid image models
by R. Gokberk Cinbis et al. is available here
Stochastic Gradient Descent for multiclass linear classification
The Stochastic Gradient Descent package mentioned in Perronnin et al. CVPR 2012
is available here
INRIA's Fisher implementation
is an implementation of Florent Perronnin
's Fisher aggregation method for local descriptors.
Dense Trajectories Video Description
The code for dense trajectories in our CVPR'11 paper - can be found on the website of Heng Wang.
Metric Learning for verification and Multiple Instance Learning
Matthieu Guillaumin's LDML and MildML on his code page
Lear's GIST implementation
This library is a C reimplementation of A. Torralba's GIST descriptor. It was used in our CIVR 2009 paper.
The weighted nearest-neighbor model for multiple binary or multiclass
classification that we successfully used it for image auto-annotation in
paper is available here.
Spatio-Temporal Descriptor for Action Recognition (HOG3D)
The software for computing the spatio-temporal descriptor using gradient orientations and regular polyhedrons (or platonic solids) - as described in our BMVC'08 paper - can be found on the website of Alexander Kläser.
Trecvid example generator
This program generates example videos for the Trecvid copy detection task.
Groups of adjacent contour segments
for detecting Vitto's local shape features (see bottom of page).
Xiaoyang Tan and Bill Triggs' MATLAB
face normalization and descriptor code, as described in our AMFG'07 paper.
YORG, developed within the AceMedia project helps organizing photo collections.
Object Detection and Localization Toolkit
You may download the Navneet Dalal's object detection and
localization toolkit from here.
and test images for Krystian Mikolajczyk's scaled and
affine interest point detectors and various types of local image
Gyuri Dorko's version of
Texture Based Image Classification
Frank Moosmann's FRIMCLA Randomized forest
based image classifier, as described in our ECCV'06 workshop
Interest Point Detectors & Test Sequences
joint comparison of affine covariant regions by LEAR, Oxford,
Leuven and Prague (the test setup and the binaries are available)