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Found 10 papers, 1 papers with code
UNITER: Learning UNiversal Image-TExt Representations
Joint image-text embedding is the bedrock for most Vision-and-Language (V+L) tasks, where multimodality inputs are jointly processed for visual and textual understanding.
UNITER: UNiversal Image-TExt Representation Learning
Different from previous work that applies joint random masking to both modalities, we use conditional masking on pre-training tasks (i. e., masked language/region modeling is conditioned on full observation of image/text).
Ranked #3 on
Visual Question Answering (VQA)
on VCR (Q-A) test
Multi-step Reasoning via Recurrent Dual Attention for Visual Dialog
This paper presents a new model for visual dialog, Recurrent Dual Attention Network (ReDAN), using multi-step reasoning to answer a series of questions about an image.
Morphological Constraints for Phrase Pivot Statistical Machine Translation
One common solution is to pivot through a third language for which there exist parallel corpora with the source and target languages.
Egyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015
The competition focused on informal dialectal Arabic, as used in SMS, chat, and speech.
MADAMIRA: A Fast, Comprehensive Tool for Morphological Analysis and Disambiguation of Arabic
In this paper, we present MADAMIRA, a system for morphological analysis and disambiguation of Arabic that combines some of the best aspects of two previously commonly used systems for Arabic processing, MADA (Habash and Rambow, 2005; Habash et al., 2009; Habash et al., 2013) and AMIRA (Diab et al., 2007).
