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20132025
most citedFoodX-251: A Dataset for Fine-grained Food Classification

66 citations · 155 across the 27 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV2019

Sunny and Dark Outside?! Improving Answer Consistency in VQA through Entailed Question Generation

Arijit Ray, Karan Sikka, Ajay Divakaran +2

While models for Visual Question Answering (VQA) have steadily improved over the years, interacting with one quickly reveals that these models lack consistency. For instance, if a…

cs.CV2019★ 66 cited

FoodX-251: A Dataset for Fine-grained Food Classification

Parneet Kaur, Karan Sikka, Weijun Wang +2

Food classification is a challenging problem due to the large number of categories, high visual similarity between different foods, as well as the lack of datasets for training sta…

cs.IR2019

Deep Unified Multimodal Embeddings for Understanding both Content and Users in Social Media Networks

Karan Sikka, Lucas Van Bramer, Ajay Divakaran

There has been an explosion of multimodal content generated on social media networks in the last few years, which has necessitated a deeper understanding of social media content an…

cs.CV2019★ 3 cited

Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts

Julia Kruk, Jonah Lubin, Karan Sikka +3

Computing author intent from multimodal data like Instagram posts requires modeling a complex relationship between text and image. For example, a caption might evoke an ironic cont…

cs.CV2019

Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment

Samyak Datta, Karan Sikka, Anirban Roy +3

We address the problem of grounding free-form textual phrases by using weak supervision from image-caption pairs. We propose a novel end-to-end model that uses caption-to-image ret…