no code implementations • 3 Jun 2024 • Sumit Sarin, Utkarsh Mall, Purva Tendulkar, Carl Vondrick
Do our facial expressions change when we speak over video calls?
1 code implementation • 26 Jan 2023 • Scott Geng, Revant Teotia, Purva Tendulkar, Sachit Menon, Carl Vondrick
We introduce a video framework for modeling the association between verbal and non-verbal communication during dyadic conversation.
no code implementations • CVPR 2023 • Purva Tendulkar, Dídac Surís, Carl Vondrick
Towards this goal, we address the task of generating a virtual human -- hands and full body -- grasping everyday objects.
no code implementations • ICCV 2023 • Ruoshi Liu, Chengzhi Mao, Purva Tendulkar, Hao Wang, Carl Vondrick
Many machine learning methods operate by inverting a neural network at inference time, which has become a popular technique for solving inverse problems in computer vision, robotics, and graphics.
1 code implementation • NAACL 2021 • Sameer Dharur, Purva Tendulkar, Dhruv Batra, Devi Parikh, Ramprasaath R. Selvaraju
Recent research in Visual Question Answering (VQA) has revealed state-of-the-art models to be inconsistent in their understanding of the world -- they answer seemingly difficult questions requiring reasoning correctly but get simpler associated sub-questions wrong.
1 code implementation • 21 Jun 2020 • Purva Tendulkar, Abhishek Das, Aniruddha Kembhavi, Devi Parikh
We encode intuitive, flexible heuristics for what a 'good' dance is: the structure of the dance should align with the structure of the music.
no code implementations • CVPR 2020 • Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh, Eric Horvitz, Marco Ribeiro, Besmira Nushi, Ece Kamar
We quantify the extent to which this phenomenon occurs by creating a new Reasoning split of the VQA dataset and collecting VQA-introspect, a new dataset1 which consists of 238K new perception questions which serve as sub questions corresponding to the set of perceptual tasks needed to effectively answer the complex reasoning questions in the Reasoning split.
1 code implementation • 19 Mar 2019 • Purva Tendulkar, Kalpesh Krishna, Ramprasaath R. Selvaraju, Devi Parikh
An approach to make text visually appealing and memorable is semantic reinforcement - the use of visual cues alluding to the context or theme in which the word is being used to reinforce the message (e. g., Google Doodles).