activity
20192023
most citedFeel The Music: Automatically Generating A Dance For An Input Song

5 citations · 14 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2023★ 3 cited

Affective Faces for Goal-Driven Dyadic Communication

Scott Geng, Revant Teotia, Purva Tendulkar +2

We introduce a video framework for modeling the association between verbal and non-verbal communication during dyadic conversation. Given the input speech of a speaker, our approac…

cs.RO2022★ 1 cited

FLEX: Full-Body Grasping Without Full-Body Grasps

Purva Tendulkar, Dídac Surís, Carl Vondrick

Synthesizing 3D human avatars interacting realistically with a scene is an important problem with applications in AR/VR, video games and robotics. Towards this goal, we address the…

cs.CV2022

Landscape Learning for Neural Network Inversion

Ruoshi Liu, Chengzhi Mao, Purva Tendulkar +2

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, robotic…

cs.CV2022★ 1 cited

Revealing Occlusions with 4D Neural Fields

Basile Van Hoorick, Purva Tendulkar, Didac Suris +3

For computer vision systems to operate in dynamic situations, they need to be able to represent and reason about object permanence. We introduce a framework for learning to estimat…

cs.CV2020

SOrT-ing VQA Models : Contrastive Gradient Learning for Improved Consistency

Sameer Dharur, Purva Tendulkar, Dhruv Batra +2

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 qu…

cs.AI2020★ 5 cited

Feel The Music: Automatically Generating A Dance For An Input Song

Purva Tendulkar, Abhishek Das, Aniruddha Kembhavi +1

We present a general computational approach that enables a machine to generate a dance for any input music. We encode intuitive, flexible heuristics for what a 'good' dance is: the…

cs.CV2020

SQuINTing at VQA Models: Introspecting VQA Models with Sub-Questions

Ramprasaath R. Selvaraju, Purva Tendulkar, Devi Parikh +4

Existing VQA datasets contain questions with varying levels of complexity. While the majority of questions in these datasets require perception for recognizing existence, propertie…

cs.CV2019★ 4 cited

Trick or TReAT: Thematic Reinforcement for Artistic Typography

Purva Tendulkar, Kalpesh Krishna, Ramprasaath R. Selvaraju +1

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 rei…