4,930 research outputs found
Oriented Response Networks
Deep Convolution Neural Networks (DCNNs) are capable of learning
unprecedentedly effective image representations. However, their ability in
handling significant local and global image rotations remains limited. In this
paper, we propose Active Rotating Filters (ARFs) that actively rotate during
convolution and produce feature maps with location and orientation explicitly
encoded. An ARF acts as a virtual filter bank containing the filter itself and
its multiple unmaterialised rotated versions. During back-propagation, an ARF
is collectively updated using errors from all its rotated versions. DCNNs using
ARFs, referred to as Oriented Response Networks (ORNs), can produce
within-class rotation-invariant deep features while maintaining inter-class
discrimination for classification tasks. The oriented response produced by ORNs
can also be used for image and object orientation estimation tasks. Over
multiple state-of-the-art DCNN architectures, such as VGG, ResNet, and STN, we
consistently observe that replacing regular filters with the proposed ARFs
leads to significant reduction in the number of network parameters and
improvement in classification performance. We report the best results on
several commonly used benchmarks.Comment: Accepted in CVPR 2017. Source code available at http://yzhou.work/OR
Generalization of form in visual pattern classification.
Human observers were trained to criterion in classifying compound Gabor signals with sym- metry relationships, and were then tested with each of 18 blob-only versions of the learning set. General- ization to dark-only and light-only blob versions of the learning signals, as well as to dark-and-light blob versions was found to be excellent, thus implying virtually perfect generalization of the ability to classify mirror-image signals. The hypothesis that the learning signals are internally represented in terms of a 'blob code' with explicit labelling of contrast polarities was tested by predicting observed generalization behaviour in terms of various types of signal representations (pixelwise, Laplacian pyramid, curvature pyramid, ON/OFF, local maxima of Laplacian and curvature operators) and a minimum-distance rule. Most representations could explain generalization for dark-only and light-only blob patterns but not for the high-thresholded versions thereof. This led to the proposal of a structure-oriented blob-code. Whether such a code could be used in conjunction with simple classifiers or should be transformed into a propo- sitional scheme of representation operated upon by a rule-based classification process remains an open question
Pre-saccadic perception: separate time courses for enhancement and spatial pooling at the saccade target
We interact with complex scenes using eye movements to select targets of interest. Studies have shown that the future target of a saccadic eye movement is processed differently by the visual system. A number of effects have been reported, including a benefit for perceptual performance at the target (“enhancement”), reduced influences of backward masking (“unmasking”), reduced crowding (“un-crowding”) and spatial compression towards the saccade target. We investigated the time course of these effects by measuring orientation discrimination for targets that were spatially crowded or temporally masked. In four experiments, we varied the target-flanker distance, the presence of forward/backward masks, the orientation of the flankers and whether participants made a saccade. Masking and randomizing flanker orientation reduced performance in both fixation and saccade trials. We found a small improvement in performance on saccade trials, compared to fixation trials, with a time course that was consistent with a general enhancement at the saccade target. In addition, a decrement in performance (reporting the average flanker orientation, rather than the target) was found in the time bins nearest saccade onset when random oriented flankers were used, consistent with spatial pooling around the saccade target. We did not find strong evidence for un-crowding. Overall, our pattern of results was consistent with both an early, general enhancement at the saccade target and a later, peri-saccadic compression/pooling towards the saccade target
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