Search Results for author: Bipasha Sen

Found 8 papers, 3 papers with code

ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning

no code implementations28 Sep 2023 Qiao Gu, Alihusein Kuwajerwala, Sacha Morin, Krishna Murthy Jatavallabhula, Bipasha Sen, Aditya Agarwal, Corban Rivera, William Paul, Kirsty Ellis, Rama Chellappa, Chuang Gan, Celso Miguel de Melo, Joshua B. Tenenbaum, Antonio Torralba, Florian Shkurti, Liam Paull

We demonstrate the utility of this representation through a number of downstream planning tasks that are specified through abstract (language) prompts and require complex reasoning over spatial and semantic concepts.

EDMP: Ensemble-of-costs-guided Diffusion for Motion Planning

1 code implementation20 Sep 2023 Kallol Saha, Vishal Mandadi, Jayaram Reddy, Ajit Srikanth, Aditya Agarwal, Bipasha Sen, Arun Singh, Madhava Krishna

However, without a prior understanding of what diverse valid trajectories are and without specially designed cost functions for a given scene, the overall solutions tend to have low success rates.

Collision Avoidance Motion Planning +1

HyP-NeRF: Learning Improved NeRF Priors using a HyperNetwork

no code implementations NeurIPS 2023 Bipasha Sen, Gaurav Singh, Aditya Agarwal, Rohith Agaram, K Madhava Krishna, Srinath Sridhar

Neural Radiance Fields (NeRF) have become an increasingly popular representation to capture high-quality appearance and shape of scenes and objects.

Retrieval

SCARP: 3D Shape Completion in ARbitrary Poses for Improved Grasping

no code implementations17 Jan 2023 Bipasha Sen, Aditya Agarwal, Gaurav Singh, Brojeshwar B., Srinath Sridhar, Madhava Krishna

Unlike existing methods that depend on an external canonicalization, SCARP performs canonicalization, pose estimation, and shape completion in a single network, improving the performance by 45% over the existing baselines.

3D Shape Generation Pose Estimation +1

INR-V: A Continuous Representation Space for Video-based Generative Tasks

1 code implementation29 Oct 2022 Bipasha Sen, Aditya Agarwal, Vinay P Namboodiri, C. V. Jawahar

In this work, we evaluate the space learned by INR-V on diverse generative tasks such as video interpolation, novel video generation, video inversion, and video inpainting against the existing baselines.

Video Generation Video Inpainting

Towards MOOCs for Lipreading: Using Synthetic Talking Heads to Train Humans in Lipreading at Scale

no code implementations21 Aug 2022 Aditya Agarwal, Bipasha Sen, Rudrabha Mukhopadhyay, Vinay Namboodiri, C. V Jawahar

Because of the manual pipeline, such platforms are also limited in vocabulary, supported languages, accents, and speakers and have a high usage cost.

Lipreading Lip Reading

FaceOff: A Video-to-Video Face Swapping System

1 code implementation21 Aug 2022 Aditya Agarwal, Bipasha Sen, Rudrabha Mukhopadhyay, Vinay Namboodiri, C. V. Jawahar

To tackle this challenge, we introduce video-to-video (V2V) face-swapping, a novel task of face-swapping that can preserve (1) the identity and expressions of the source (actor) face video and (2) the background and pose of the target (double) video.

Face Swapping

Personalized One-Shot Lipreading for an ALS Patient

no code implementations2 Nov 2021 Bipasha Sen, Aditya Agarwal, Rudrabha Mukhopadhyay, Vinay Namboodiri, C V Jawahar

Apart from evaluating our approach on the ALS patient, we also extend it to people with hearing impairment relying extensively on lip movements to communicate.

Domain Adaptation Lipreading

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