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Found 3 papers, 1 papers with code
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
Top-down visual attention mechanisms have been used extensively in image captioning and visual question answering (VQA) to enable deeper image understanding through fine-grained analysis and even multiple steps of reasoning.
Ranked #29 on
Visual Question Answering (VQA)
on VQA v2 test-std
Semantic-driven Generation of Hyperlapse from $360^\circ$ Video
We present a system for converting a fully panoramic ($360^\circ$) video into a normal field-of-view (NFOV) hyperlapse for an optimal viewing experience.
Rich Image Captioning in the Wild
We present an image caption system that addresses new challenges of automatically describing images in the wild.
