8 citations · 12 across the 7 of their papers we have counts for
5 papers · 1 filter
Analyzing Modular Approaches for Visual Question Decomposition
Apoorv Khandelwal, Ellie Pavlick, Chen Sun
Modular neural networks without additional training have recently been shown to surpass end-to-end neural networks on challenging vision-language tasks. The latest such methods sim…
What's in a Decade? Transforming Faces Through Time
Eric Ming Chen, Jin Sun, Apoorv Khandelwal +3
How can one visually characterize people in a decade? In this work, we assemble the Faces Through Time dataset, which contains over a thousand portrait images from each decade, spa…
A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge
Dustin Schwenk, Apoorv Khandelwal, Christopher Clark +2
The Visual Question Answering (VQA) task aspires to provide a meaningful testbed for the development of AI models that can jointly reason over visual and natural language inputs. D…
Simple but Effective: CLIP Embeddings for Embodied AI
Apoorv Khandelwal, Luca Weihs, Roozbeh Mottaghi +1
Contrastive language image pretraining (CLIP) encoders have been shown to be beneficial for a range of visual tasks from classification and detection to captioning and image manipu…
Who's Waldo? Linking People Across Text and Images
Claire Yuqing Cui, Apoorv Khandelwal, Yoav Artzi +2
We present a task and benchmark dataset for person-centric visual grounding, the problem of linking between people named in a caption and people pictured in an image. In contrast t…