Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering

A number of studies have found that today's Visual Question Answering (VQA) models are heavily driven by superficial correlations in the training data and lack sufficient image grounding. To encourage development of models geared towards the latter, we propose a new setting for VQA where for every question type, train and test sets have different prior distributions of answers. Specifically, we present new splits of the VQA v1 and VQA v2 datasets, which we call Visual Question Answering under Changing Priors (VQA-CP v1 and VQA-CP v2 respectively). First, we evaluate several existing VQA models under this new setting and show that their performance degrades significantly compared to the original VQA setting. Second, we propose a novel Grounded Visual Question Answering model (GVQA) that contains inductive biases and restrictions in the architecture specifically designed to prevent the model from 'cheating' by primarily relying on priors in the training data. Specifically, GVQA explicitly disentangles the recognition of visual concepts present in the image from the identification of plausible answer space for a given question, enabling the model to more robustly generalize across different distributions of answers. GVQA is built off an existing VQA model -- Stacked Attention Networks (SAN). Our experiments demonstrate that GVQA significantly outperforms SAN on both VQA-CP v1 and VQA-CP v2 datasets. Interestingly, it also outperforms more powerful VQA models such as Multimodal Compact Bilinear Pooling (MCB) in several cases. GVQA offers strengths complementary to SAN when trained and evaluated on the original VQA v1 and VQA v2 datasets. Finally, GVQA is more transparent and interpretable than existing VQA models.Comment: 15 pages, 10 figures. To appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 201

On the origin of the featureless soft X-ray excess emission from the Seyfert 1 galaxy ESO~198--G24

We present medium and high resolution X-ray spectral study of a Seyfert 1 galaxy ESO~198--G24 using a long (122 ks) XMM-Newton observation performed in February 2006. The source has a prominent featureless soft X-ray excess below 2\kev. This makes the source well suited to investigate the origin of the soft excess. Two physical models -- blurred reflection, and optically thick thermal Comptonization in a warm plasma, describe the soft-excess equally well resulting in similar fits in the 0.3-10\kev band. These models also yield similar fits to the broad-band UV (Optical Monitor) and X-ray data. XMM-Newton observations performed in 2000, 2001 and 2006 on this source show flux variability. From 2001 to 2006, the UV flux increased by $\sim23\%$ while the 2-10\kev X-ray flux as well as the soft-excess flux decreased by ~ 20. This observation can be described in the blurred reflection scenario by a truncated accretion disk whose inner-most radius had come closer to the blackhole. We find that the best-fit inner radius of the accretion disk decreases from R_{in}=4.93_{-1.10}^{+1.12}R_G to R_{in}<2.5R_G from 2001 to 2006. This leads to an increase in the UV flux and compressing the corona, leading to reduction of the powerlaw flux and therefore the soft-excess. The blurred reflection model seems to better describe the soft-excess for this source.Comment: Accepted for publication in the MNRA

Recognizing Objects And Reasoning About Their Interactions

The task of scene understanding involves recognizing the different objects present in the scene, segmenting the scene into meaningful regions, as well as obtaining a holistic understanding of the activities taking place in the scene. Each of these problems has received considerable interest within the computer vision community. We present contributions to two aspects of visual scene understanding. First we explore multiple methods of feature selection for the problem of object detection. We demonstrate the use of Principal Component Analysis to detect avifauna in field observation videos. We improve on existing approaches by making robust decisions based on regional features and by a feature selection strategy that chooses different features in different parts of the image. We then demonstrate the use of Partial Least Squares to detect vehicles in aerial and satellite imagery. We propose two new feature sets; Color Probability Maps are used to capture the color statistics of vehicles and their surroundings, and Pairs of Pixels are used to capture captures the structural characteristics of objects. A powerful feature selection analysis based on Partial Least Squares is employed to deal with the resulting high dimensional feature space (almost 70,000 dimensions). We also propose an Incremental Multiple Kernel Learning (IMKL) scheme to detect vehicles in a traffic surveillance scenario. Obtaining task and scene specific datasets of visual categories is far more tedious than obtaining a generic dataset of the same classes. Our IMKL approach initializes on a generic training database and then tunes itself to the classification task at hand. Second, we develop a video understanding system for scene elements, such as bus stops, crosswalks, and intersections, that are characterized more by qualitative activities and geometry than by intrinsic appearance. The domain models for scene elements are not learned from a corpus of video, but instead, naturally elicited by humans, and represented as probabilistic logic rules within a Markov Logic Network framework. Human elicited models, however, represent object interactions as they occur in the 3D world rather than describing their appearance projection in some specific 2D image plane. We bridge this gap by recovering qualitative scene geometry to analyze object interactions in the 3D world and then reasoning about scene geometry, occlusions and common sense domain knowledge using a set of meta-rules

Perceptions of participation and inclusion among adolescents with disabilities: experiences from South India

Disability is an issue of human rights and equal opportunity and is no longer focused on impairment and medical intervention. Adolescents with disabilities (AWD) are marginalised throughout the world (UNICEF, 2005), particularly in low- and middle-income countries where they are affected by poor access to resources, and by stigma and local taboos. Poverty has been shown to accentuate the impact of disability. The cycle of poverty and disability is marked by poor access to education, vocational training, and employment. The need of AWD for inclusion and participation in education, health and social life are the same as their non-disabled peers. For many AWD, these needs continue to go unmet (Groce, 2004). The research question was: ‘How do adolescents with physical disabilities perceive the factors that determine their participation and inclusion in their communities in South India?’ Quantitative and qualitative techniques were used. Thirty-seven AWD, 25 parents of AWD, and 24 non-disabled adolescent peers participated in the study in Bangalore, India. A background information questionnaire and two measures of quality of life (QOL) were conducted with all participants. Qualitative data was gathered with each participant group using interviews and focus group discussions (FGD). Photography was used with the AWD to facilitate discussions. Analysis of QOL data revealed no differences between AWD and parent-proxy scores. Differences exist in QOL scores between AWD and their peers. Analysis of interview and FGD data revealed three key themes that influence the perception of Participation and Inclusion among AWD. These are: 1) Personal Factors; 2) Interpersonal Relationships; and 3) External Factors. Belief in themselves and parental support were two key facilitators of participation. Negative attitudes of others, physical barriers, and poorly implemented legislation were significant barriers to participation. Recommendations are suggested to enhance the participation and inclusion of AWD and to facilitate success in adulthood

A Study of Quasar Radio Emission from the VLA FIRST Survey

Using the most recent (1998) version of the VLA FIRST survey radio catalog, we have searched for radio emission from 1704 quasars taken from the most recent (1993) version of the Hewitt and Burbidge quasar catalog. These quasars lie in the ~5000 square degrees of sky already covered by the VLA FIRST survey. Our work has resulted in positive detection of radio emission from 389 quasars of which 69 quasars have been detected for the first time at radio wavelengths. We find no evidence of correlation between optical and radio luminosities for optically selected quasars. We find indications of a bimodal distribution of radio luminosity, even at a low flux limit of 1 mJy. We show that radio luminosity is a good discriminant between radio loud and radio quiet quasar populations, and that it may be inappropriate to make such a division on the basis of the radio to optical luminosity ratio. We discuss the dependence of the radio loud fraction on optical luminosity and redshift.Comment: 33 pages LaTeX, 10 figures, 2 tables. Accepted in the Astronomical Journa

Studies of the optical model for elastic scattering.

Optical model studies of medium energy alpha particles and high energy pions using the microscopic model, are carried out to investigate the nuclear matter distribution. For medium energy alpha particles, the optical potentials are obtained by folding an effective alpha-nucleon interaction into the nuclear matter distributions which are constructed from single particle wave functions, and elastic scattering of alpha particles at 42 MeV is calculated. It is shown that the nuclear matter distributions obtained as above can explain reasonably well experimental data, if a suitable form for the effective interaction is chosen. Further, the ability of the microscopic model to reproduce the observed behaviour of the strong absorption radii, is examined and it is found that the strong absorption radii obtained, show systematic A-dependence. But it is noted that the small uncertainties in the range parameter of the effective interaction become significant when one is concerned with the precise behaviour of these radii. The same uncertainties also limit the accurate determination of the nuclear matter distribution. For high energy pions, the optical potentials are obtained by folding the free pion-nucleon interaction in momentum space into the nucleon form factors which are calculated using neutron and proton distributions obtained as before. Using these pion optical potentials, the Klein-Gordon equation is solved numerically and the absorption and differential cross-sections at energies in the region 0.585-1.057 GeV are calculated. These calculations are carried out using the complete expression for the pion-nucleon interaction as well as the large A approximation. It is shown that the absorption and differential cross-sections for light and medium mass nuclei are quite sensitive to the variations in the parameters of the pion optical potential and in particular, at the minima in the differential cross-sections, significant changes are produced. From a comparison of our results for the absorption cross-sections for such nuclei with some available experimental data, it is indicated that the use of the large A approximation may significantly alter the conclusions reached before about the nuclear matter distributions. It also appears that even for heavy nuclei, the use of this approximation is probably suspect, especially when one is concerned with the analysis of accurate experimental data