Revisiting knowledge transfer for training object class detectors

We propose to revisit knowledge transfer for training object detectors on target classes from weakly supervised training images, helped by a set of source classes with bounding-box annotations. We present a unified knowledge transfer framework based on training a single neural network multi-class object detector over all source classes, organized in a semantic hierarchy. This generates proposals with scores at multiple levels in the hierarchy, which we use to explore knowledge transfer over a broad range of generality, ranging from class-specific (bicycle to motorbike) to class-generic (objectness to any class). Experiments on the 200 object classes in the ILSVRC 2013 detection dataset show that our technique: (1) leads to much better performance on the target classes (70.3% CorLoc, 36.9% mAP) than a weakly supervised baseline which uses manually engineered objectness [11] (50.5% CorLoc, 25.4% mAP). (2) delivers target object detectors reaching 80% of the mAP of their fully supervised counterparts. (3) outperforms the best reported transfer learning results on this dataset (+41% CorLoc and +3% mAP over [18, 46], +16.2% mAP over [32]). Moreover, we also carry out several across-dataset knowledge transfer experiments [27, 24, 35] and find that (4) our technique outperforms the weakly supervised baseline in all dataset pairs by 1.5x-1.9x, establishing its general applicability.Comment: CVPR 1

Normality in terms of distances and contractions

The main purpose of this paper is to explore normality in terms of distances between points and sets. We prove some important consequences on realvalued contractions, i.e. functions not enlarging the distance, showing that as in the classical context of closures and continuous maps, normality in terms of distances based on an appropriate numerical notion of $\gamma$-separation of sets, has far reaching consequences on real valued contractive maps, where the real line is endowed with the Euclidean metric. We show that normality is equivalent to (1) separation of $\gamma$-separated sets by some Urysohn contractive map, (2) to Kat\v{e}tov-Tong's interpolation, stating that for bounded positive realvalued functions, between an upper and a larger lower regular function, there exists a contractive interpolating map and (3) to Tietze's extension theorem stating that certain contractions defined on a subspace can be contractively extended to the whole space. The appropriate setting for these investigations is the category of approach spaces, but the results have (quasi)-metric counterparts in terms of non-expansive maps. Moreover when restricted to topological spaces, classical normality and its equivalence to separation by a Urysohn continuous map, to Kat\v{e}tov-Tong's interpolation for semicontinuous maps and to Tietze's extension theorem for continuous maps are recovered

Hydrodynamic simulations of correlation and scatter in galaxy cluster maps

The two dimensional structure of hot gas in galaxy clusters contains information about the hydrodynamical state of the cluster, which can be used to understand the origin of scatter in the thermodynamical properties of the gas, and to improve the use of clusters to probe cosmology. Using a set of hydrodynamical simulations, we provide a comparison between various maps currently employed in the X-ray analysis of merging clusters and those cluster maps anticipated from forthcoming observations of the thermal Sunyaev-Zel'dovich effect. We show the following: 1) an X-ray pseudo-pressure, defined as square root of the soft band X-ray image times the temperature map is a good proxy for the SZ map; 2) we find that clumpiness is the main reason for deviation between X-ray pseudo-pressure and SZ maps; 3) the level of clumpiness can be well characterized by X-ray pseudo-entropy maps. 4) We describe the frequency of deviation in various maps of clusters as a function of the amplitude of the deviation. This enables both a comparison to observations and a comparison to effects of introduction of complex physical processes into simulation.Comment: 7 pages, A&A in pres

Addendum to "Amitsur's complex for purely inseparable fields"

We begin this note by pointing out that a few modifications in some of the notations and arguments of C131 will make these fit in more closely with results in the literature. We also complete the results of C131 in several points. In particular we point out that the spectral sequence used in C131 is not quite a genuine generalization of the Hochschild-Serre spectral sequence in Galois cohomology. However with a slightly different spectral sequence the results of C131 can also be obtained and we shall show in section 2 that this is indeed a genuine generalization of the Hochschild-Serre sequence for Galois cohomology. In section 3 we shall use some of the results of [13] to derive an exact sequence complementary to that of Proposition 7.8 of [13] from which we deduce the following result first pointed out to us by S. Shatz: Let C be a field, C, its separable algebraic closure and its algebraic closure. Then if X is the lift map [2, Def. 2. 3.1, we have that X : Hr(C,/C)- . ~ ' ( 6 1is~ ) an isomorphism for r = 1,2, ..

Genetical genomics dissection of cotton fiber quality

Cotton fiber is a commodity of key economic importance in both developed and developing countries. The two cultivated species, Gossypium hirsutum and G. barbadense , are tetraploid (2n=1x= 52 . 2.3 Gb). Cotton fibers are single-celled trichomes of the outermost epidermallayer of the ovule and elongate extensively to 25-50 mm. The final quality of the fiber results from complex developmentai processes and improvement of cotton fiber quality remains a challenge for many research groups worldwide. Although traditional breeding methods have proven efficient, the contribution of molecular genetics and genomic tools are gaining interest and the cotton fiber transcriptome has attracted a lot of attention in recent years. The major objective of the project (acronym Cotton_RILs) sponsored by the French National Research Agency (ANR) , is the genetic and genomic dissection of important fiber quality characteristics using a combination of classical QTL mapping and of gene expression QTL mapping. The integrated genetics and genomics approach (or genetical genomics approach) in this project is centered on a population of interspecific G. hirsutum X G. harhadense recombinant inbred lines (RILs) created by CIRAD. Specifie objectives are, 1. Construction of a saturated genetic map, 2. QTL mapping through multi-site phenotypic evaluation on 1 continents. 3. Population-wide gene expression analysis through microarray and cDNA-AFLP profilings and for 1 or 2 key developmental stages, and 4. Genetic fine mapping of selected QTLs using a large F, population. The 3 participants in the project. CIRAD (Montpellier, France) . Bayer Crop Science (Gent . Belgium). and CSIRü (Canberra , Australia) , have active research programs in applied genetics both through c1assical breeding and using modern biotechnology. Past achievements of the 3 laboratories are recognized worldwide and they are highly complementary in terms of their scientific expertise. Apart from greenhouses and biotechnology laboratories in their respective primary sites, they provide access to a broad range of field experimental sites on 4 continents, in Brazil and Cameroon through CIRAD partnerships and in the USA for Bayer CS. (Texte intégral