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Found 9 papers, 1 papers with code
Answer Mining from a Pool of Images: Towards Retrieval-Based Visual Question Answering
We study visual question answering in a setting where the answer has to be mined from a pool of relevant and irrelevant images given as a context.
Determinantal Point Process as an alternative to NMS
We present a determinantal point process (DPP) inspired alternative to non-maximum suppression (NMS) which has become an integral step in all state-of-the-art object detection frameworks.
Agriculture Commodity Arrival Prediction using Remote Sensing Data: Insights and Beyond
In developing countries like India agriculture plays an extremely important role in the lives of the population.
$c^+$GAN: Complementary Fashion Item Recommendation
We present a conditional generative adversarial model to draw realistic samples from paired fashion clothing distribution and provide real samples to pair with arbitrary fashion units.
Re-evaluating ADEM: A Deeper Look at Scoring Dialogue Responses
ADEM(Lowe et al. 2017) formulated the automatic evaluation of dialogue systems as a learning problem and showed that such a model was able to predict responses which correlate significantly with human judgements, both at utterance and system level.
Doc2Im: document to image conversion through self-attentive embedding
In this paper we propose a completely novel direction to text classification research, wherein we convert text to a representation very similar to images, such that any deep network able to handle images is equally able to handle text.
Solve-Select-Scale: A Three Step Process For Sparse Signal Estimation
In the theory of compressed sensing (CS), the sparsity $\|x\|_0$ of the unknown signal $\mathbf{x} \in \mathcal{R}^n$ is of prime importance and the focus of reconstruction algorithms has mainly been either $\|x\|_0$ or its convex relaxation (via $\|x\|_1$).
KL Divergence Based Agglomerative Clustering for Automated Vitiligo Grading
In this paper we present a symmetric KL divergence based agglomerative clustering framework to segment multiple levels of depigmentation in Vitiligo images.
Bregman Distance to L1 Regularized Logistic Regression
In this work we investigate the relationship between Bregman distances and regularized Logistic Regression model.
