CASENet: Deep Category-Aware Semantic Edge Detection

Boundary and edge cues are highly beneficial in improving a wide variety of vision tasks such as semantic segmentation, object recognition, stereo, and object proposal generation. Recently, the problem of edge detection has been revisited and significant progress has been made with deep learning. While classical edge detection is a challenging binary problem in itself, the category-aware semantic edge detection by nature is an even more challenging multi-label problem. We model the problem such that each edge pixel can be associated with more than one class as they appear in contours or junctions belonging to two or more semantic classes. To this end, we propose a novel end-to-end deep semantic edge learning architecture based on ResNet and a new skip-layer architecture where category-wise edge activations at the top convolution layer share and are fused with the same set of bottom layer features. We then propose a multi-label loss function to supervise the fused activations. We show that our proposed architecture benefits this problem with better performance, and we outperform the current state-of-the-art semantic edge detection methods by a large margin on standard data sets such as SBD and Cityscapes.Comment: Accepted to CVPR 201

Molecular gas in high-velocity clouds: revisited scenario

We report a new search for 12CO(1-0) emission in high-velocity clouds (HVCs) performed with the IRAM 30 m telescope. This search was motivated by the recent detection of cold dust emission in the HVCs of Complex C. Despite a spatial resolution which is three times better and sensitivity twice as good compared to previous studies, no CO emission is detected in the HVCs of Complex C down to a best 5 sigma limit of 0.16 K km/s at a 22'' resolution. The CO emission non-detection does not provide any evidence in favor of large amounts of molecular gas in these HVCs and hence in favor of the infrared findings. We discuss different configurations which, however, allow us to reconcile the negative CO result with the presence of molecular gas and cold dust emission. H2 column densities higher than our detection limit, N(H2) = 3x10^{19} cm^{-2}, are expected to be confined in very small and dense clumps with 20 times smaller sizes than the 0.5 pc clumps resolved in our observations according to the results obtained in cirrus clouds, and might thus still be highly diluted. As a consequence, the inter-clump gas at the 1 pc scale has a volume density lower than 20 cm^{-3} and already appears as too diffuse to excite the CO molecules. The observed physical conditions in the HVCs of Complex C also play an important role against CO emission detection. It has been shown that the CO-to-H2 conversion factor in low metallicity media is 60 times higher than at the solar metallicity, leading for a given H2 column density to a 60 times weaker integrated CO intensity. And the very low dust temperature estimated in these HVCs implies the possible presence of gas cold enough (< 20 K) to cause CO condensation onto dust grains under interstellar medium pressure conditions and thus CO depletion in gas-phase observations.Comment: 9 pages, 4 figures, Accepted for publication in A&

Recovery of edges from spectral data with noise -- a new perspective

We consider the problem of detecting edges in piecewise smooth functions from their N-degree spectral content, which is assumed to be corrupted by noise. There are three scales involved: the "smoothness" scale of order 1/N, the noise scale of order $\eta$ and the O(1) scale of the jump discontinuities. We use concentration factors which are adjusted to the noise variance, $\eta$ >> 1/N, in order to detect the underlying O(1)-edges, which are separated from the noise scale, $\eta$ << 1

Viking Lander 1 and 2 revisited: The characterisation and detection of Martian dust devils

Dust devil data from Mars is limited by a lack of data relating to diurnal dust devil behaviour. The meteorological data from the Viking landers has been revisited to provide these diurnal statistics

Edge-detection applied to moving sand dunes on Mars

Here we discuss the application of an edge detection filter, the Sobel filter of GIMP, to the recently discovered motion of some sand dunes on Mars. The filter allows a good comparison of an image HiRISE of 2007 and an image of 1999 recorded by the Mars Global Surveyor of the dunes in the Nili Patera caldera, measuring therefore the motion of the dunes on a longer period of time than that previously investigated.Comment: Keywords: Edge detection, Sobel filter, GIMP, Image processing, Google Mars, Dune motion, Mars Reconnaissance Orbiter, Mars Global Surveyor; Ref.14 available at http://www.scribd.com/doc/162390676/Moving-Sand-Dunes-on-Mar