CBCL
SOFTWARE:
- Models of Object
Recognition:
Over the years, CBCL has written a number of different software packages
implementing hierarchical models of object recognition (dubbed "HMAX" models) which are
inspired by the ventral visual pathway.
The most comprehensive description of this class of models
is "A Theory of Object Recognition: Computations and
Circuits in the Feedforward Path of the Ventral Stream in
Primate Visual Cortex"
[Serre, Kouh, Cadieu, Knoblich, Kreiman, and Poggio (2005)]. The
table below has links to downloadable software.
| Description | Circa | Paper |
|---|
| CNS ("Cortical Network Simulator")
A general GPU-based framework for the fast simulation of "cortically-organized" networks, defined as networks consisting of
n-dimensional layers of similar cells.
This is a fairly broad class, including more than just "HMAX" models. We have developed specialized CNS packages for
HMAX feature hierarchy models (hmax),
convolutional networks (cnpkg), and
networks of Hodgkin-Huxley spiking cells (hhpkg).
While CNS is designed for use with a GPU, it can run (much more slowly) without one. It does, however,
require MATLAB.
| 2010
| Mutch, Knoblich, & Poggio (2010) |
| hmin: A Minimal HMAX Implementation
This is a simple reference implementation of HMAX, meant for illustration. It is a single-threaded, CPU-based,
pure C++ implementation (but still called via MATLAB's "mex" interface).
The package contains C++ classes for layers and filters, and a main program that assembles them to implement
one specific model.
| 2010 |
|
-
System for Mouse Behavior Recognition
| Description |
Circa |
Paper |
The system consists of two modules: a feature computation module, and a classification module. The feature computation module is based on a biologically-inspired dorsal stream model, which is, in turn, inspired by the ventral stream model (Models of Object Recognition). The classifier in the classification module is SVMhmm
| 2010
| Jhuang, Garrote, Yu, Khilnani, Poggio, Steele, Serre (Nat. Comms. 2010) |
-
Regularized Least-Squares MATLAB Toolkit
- LEGACY SOFTWARE:
(these packages are no longer actively used within CBCL)
| Description | Circa | Paper |
|---|
"Bypass route only" code
A pure MATLAB implementation of the four-layer (S1->C2b) "bypass route" model.
| 2005
| Serre,
Wolf & Poggio (CVPR 2005)
Serre,
Wolf, Bileschi, Riesenhuber & Poggio (PAMI 2007) |
Code for experiments replicating human performance in
the animal/no-animal rapid scene categorization task. Written using FHLib (below).
| 2007
| Serre,
Oliva & Poggio (PNAS 2007)
Serre,
Kouh, Cadieu, Knoblich, Kreiman & Poggio (AI memo 2005) |
|
FHLib - Multiscale Feature Hierarchy Library
A rather general framework that allows the definition of feedforward hierarchies having an arbitrary
number of levels. MATLAB interface with a C++ back-end (CPU-based) for efficiency. Arbitrary filter kernels can
be defined, but this requires creating new C++ classes and recompiling. This code is fairly well documented.
| 2007
|
Mutch & Lowe (IJCV 2008) |
|
Model of object recognition with canonical normalization operations
Like FHLib, allows feedforward hierarchies of arbitrary depth, and is also MATLAB with a C++ (CPU-based) back-end.
Defining new filters is easier than under FHLib, but all filters must be of the form
y = sum(f .* (x .^ p)) / (c + sum(f .* (x .^ q)) .^ r). Different settings
of c, p, q, and r correspond to tuning, softmax, etc. Models run more slowly than under FHLib.
| 2006
|
Kouh & Poggio (Neural Comp. 2008)
Zoccolan et al. (J. Neurosci. 2007)
Cadieu, et al. (J. Neurophys. 2007) |
| Original "HMAX" code
This model implementation is now obsolete and is no longer distributed.
| 1999
| Riesenhuber
and Poggio (Nat. Neurosci. 1999) |
CBCL DATASETS:
CBCL
SUPPLEMENTARY MATERIAL:
The CBCL data sets are
covered by the following copyright.
Copyright
2000
Center for Biological & Computational Learning at
MIT and MIT
All rights reserved.
Permission to copy and modify this data, software, and
its documentation only for internal research use in your
organization is hereby granted, provided that this notice
is retained thereon and on all copies. This data and software
should not be distributed to anyone outside of your organization
without explicit written authorization by the author(s)
and MIT. It should not be used for commercial purposes
without specific permission from the authors and MIT.
MIT also requires written authorization by the author(s)
to publish results obtained with the data or software
and possibly citation of relevant CBCL reference papers.
We make no representation as to the suitability and operability
of this data or software for any purpose. It is provided
"as is" without express or implied warranty.
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