1 code implementation • 16 Aug 2023 • Georgios Kouros, Minye Wu, Shubham Shrivastava, Sushruth Nagesh, Punarjay Chakravarty, Tinne Tuytelaars
To this end, we investigate an implicit-explicit approach based on conventional volume rendering to enhance the reconstruction quality and accelerate the training and rendering processes.
no code implementations • 30 Jun 2023 • Stephen Hausler, Sourav Garg, Punarjay Chakravarty, Shubham Shrivastava, Ankit Vora, Michael Milford
In this work we investigate whether a prior map can be leveraged to aid in the detection of dynamic objects in a scene without the need for a 3D map or pixel-level map-query correspondences.
no code implementations • 30 Jun 2023 • Stephen Hausler, Sourav Garg, Punarjay Chakravarty, Shubham Shrivastava, Ankit Vora, Michael Milford
In this research, we propose a middle ground, demonstrated in the context of autonomous vehicles, using dynamic vehicles to provide limited pose constraint information in a 6-DoF frame-by-frame PnP-RANSAC localization pipeline.
2 code implementations • 5 Oct 2022 • Cédric Picron, Punarjay Chakravarty, Tinne Tuytelaars
Recently, two-stage Deformable DETR introduced the query-based two-stage head, a new type of two-stage head different from the region-based two-stage heads of classical detectors as Faster R-CNN.
1 code implementation • 12 Aug 2022 • Georgios Kouros, Shubham Shrivastava, Cédric Picron, Sushruth Nagesh, Punarjay Chakravarty, Tinne Tuytelaars
In both cases, the idea is to directly predict the pose of an object.
no code implementations • 28 Jun 2022 • Stephen Hausler, Ming Xu, Sourav Garg, Punarjay Chakravarty, Shubham Shrivastava, Ankit Vora, Michael Milford
6-DoF visual localization systems utilize principled approaches rooted in 3D geometry to perform accurate camera pose estimation of images to a map.
no code implementations • 20 Jun 2022 • Zhengxia Zou, Rusheng Zhang, Shengyin Shen, Gaurav Pandey, Punarjay Chakravarty, Armin Parchami, Henry X. Liu
We propose a novel and pragmatic framework for traffic scene perception with roadside cameras.
no code implementations • 17 Jun 2022 • Sinnu Susan Thomas, Jacopo Palandri, Mohsen Lakehal-ayat, Punarjay Chakravarty, Friedrich Wolf-Monheim, Matthew B. Blaschko
We show that the proposed approach is general, scalable, and efficient, and that the novel convergence criteria can be implemented straightforwardly based on existing concepts and subroutines in popular Bayesian optimization software packages.
1 code implementation • 7 Oct 2021 • Boris Ivanovic, Yifeng Lin, Shubham Shrivastava, Punarjay Chakravarty, Marco Pavone
As a result, perceptual uncertainties are not propagated through forecasting and predictions are frequently overconfident.
no code implementations • ICCV 2021 • Yunfei Long, Daniel Morris, Xiaoming Liu, Marcos Castro, Punarjay Chakravarty, Praveen Narayanan
A distinctive feature of Doppler radar is the measurement of velocity in the radial direction for radar points.
no code implementations • CVPR 2021 • Yunfei Long, Daniel Morris, Xiaoming Liu, Marcos Castro, Punarjay Chakravarty, Praveen Narayanan
Here we propose a radar-to-pixel association stage which learns a mapping from radar returns to pixels.
no code implementations • 23 Jan 2021 • Mokshith Voodarla, Shubham Shrivastava, Sagar Manglani, Ankit Vora, Siddharth Agarwal, Punarjay Chakravarty
We describe a light-weight, weather and lighting invariant, Semantic Bird's Eye View (S-BEV) signature for vision-based vehicle re-localization.
no code implementations • 5 Jan 2021 • Kaushik Balakrishnan, Punarjay Chakravarty, Shubham Shrivastava
Training robots to navigate diverse environments is a challenging problem as it involves the confluence of several different perception tasks such as mapping and localization, followed by optimal path-planning and control.
1 code implementation • 1 Dec 2020 • Nithin Raghavan, Punarjay Chakravarty, Shubham Shrivastava
Image-based learning methods for autonomous vehicle perception tasks require large quantities of labelled, real data in order to properly train without overfitting, which can often be incredibly costly.
no code implementations • 29 Jul 2020 • Cédric Picron, Punarjay Chakravarty, Tom Roussel, Tinne Tuytelaars
We subsequently demonstrate an optimization-based monocular 3D bounding box detector built on top of the self-supervised vehicle orientation estimator without the requirement of expensive labeled data.
no code implementations • 7 Jun 2020 • Shubham Shrivastava, Punarjay Chakravarty
We introduce a method for 3D object detection using a single monocular image.
3D Object Detection From Monocular Images Autonomous Vehicles +3
no code implementations • 28 Apr 2020 • Nikita Jaipuria, Xianling Zhang, Rohan Bhasin, Mayar Arafa, Punarjay Chakravarty, Shubham Shrivastava, Sagar Manglani, Vidya N. Murali
Deep Learning has seen an unprecedented increase in vision applications since the publication of large-scale object recognition datasets and introduction of scalable compute hardware.
no code implementations • 4 Feb 2020 • Tom Roussel, Punarjay Chakravarty, Gaurav Pandey, Tinne Tuytelaars, Luc Van Eycken
We describe a Deep-Geometric Localizer that is able to estimate the full 6 Degree of Freedom (DoF) global pose of the camera from a single image in a previously mapped environment.
3 code implementations • ECCV 2020 • Tim Salzmann, Boris Ivanovic, Punarjay Chakravarty, Marco Pavone
Reasoning about human motion is an important prerequisite to safe and socially-aware robotic navigation.
Ranked #2 on Trajectory Prediction on ETH
no code implementations • 15 Jul 2019 • Praveen Narayanan, Punarjay Chakravarty, Francois Charette, Gint Puskorius
Our seq2seq architecture makes use of a hierarchical encoder to summarize input audio frames.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +7
no code implementations • 6 Feb 2019 • Punarjay Chakravarty, Praveen Narayanan, Tom Roussel
We present a Deep Learning based system for the twin tasks of localization and obstacle avoidance essential to any mobile robot.
no code implementations • 28 Nov 2016 • Rahaf Aljundi, Punarjay Chakravarty, Tinne Tuytelaars
In this work, we aim at automatically labeling actors in a TV series.
2 code implementations • CVPR 2017 • Rahaf Aljundi, Punarjay Chakravarty, Tinne Tuytelaars
Further, the autoencoders inherently capture the relatedness of one task to another, based on which the most relevant prior model to be used for training a new expert, with finetuning or learning without-forgetting, can be selected.
no code implementations • 29 Mar 2016 • Punarjay Chakravarty, Tinne Tuytelaars
We further improve a generic model for active speaker detection by learning person specific models.