Search Results for author: Rohan Chandra

Found 16 papers, 10 papers with code

M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers

1 code implementation24 Apr 2021 Tianrui Guan, Jun Wang, Shiyi Lan, Rohan Chandra, Zuxuan Wu, Larry Davis, Dinesh Manocha

We present a novel architecture for 3D object detection, M3DeTR, which combines different point cloud representations (raw, voxels, bird-eye view) with different feature scales based on multi-scale feature pyramids.

3D Object Detection object-detection

GANav: Efficient Terrain Segmentation for Robot Navigation in Unstructured Outdoor Environments

1 code implementation7 Mar 2021 Tianrui Guan, Divya Kothandaraman, Rohan Chandra, Adarsh Jagan Sathyamoorthy, Kasun Weerakoon, Dinesh Manocha

We interface GANav with a deep reinforcement learning-based navigation algorithm and highlight its benefits in terms of navigation in real-world unstructured terrains.

Robot Navigation Semantic Segmentation

B-GAP: Behavior-Rich Simulation and Navigation for Autonomous Driving

3 code implementations7 Nov 2020 Angelos Mavrogiannis, Rohan Chandra, Dinesh Manocha

We address the problem of ego-vehicle navigation in dense simulated traffic environments populated by road agents with varying driver behaviors.


Emotions Don't Lie: An Audio-Visual Deepfake Detection Method Using Affective Cues

no code implementations14 Mar 2020 Trisha Mittal, Uttaran Bhattacharya, Rohan Chandra, Aniket Bera, Dinesh Manocha

Additionally, we extract and compare affective cues corresponding to perceived emotion from the two modalities within a video to infer whether the input video is "real" or "fake".

DeepFake Detection Face Swapping

Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs

no code implementations arXiv 2019 Rohan Chandra, Tianrui Guan, Srujan Panuganti, Trisha Mittal, Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha

In practice, our approach reduces the average prediction error by more than 54% over prior algorithms and achieves a weighted average accuracy of 91. 2% for behavior prediction.


M3ER: Multiplicative Multimodal Emotion Recognition Using Facial, Textual, and Speech Cues

no code implementations9 Nov 2019 Trisha Mittal, Uttaran Bhattacharya, Rohan Chandra, Aniket Bera, Dinesh Manocha

Our approach combines cues from multiple co-occurring modalities (such as face, text, and speech) and also is more robust than other methods to sensor noise in any of the individual modalities.

Multimodal Emotion Recognition

STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

1 code implementation28 Oct 2019 Uttaran Bhattacharya, Trisha Mittal, Rohan Chandra, Tanmay Randhavane, Aniket Bera, Dinesh Manocha

We use hundreds of annotated real-world gait videos and augment them with thousands of annotated synthetic gaits generated using a novel generative network called STEP-Gen, built on an ST-GCN based Conditional Variational Autoencoder (CVAE).

General Classification

RobustTP: End-to-End Trajectory Prediction for Heterogeneous Road-Agents in Dense Traffic with Noisy Sensor Inputs

1 code implementation20 Jul 2019 Rohan Chandra, Uttaran Bhattacharya, Christian Roncal, Aniket Bera, Dinesh Manocha

RobustTP is an approach that first computes trajectories using a combination of a non-linear motion model and a deep learning-based instance segmentation algorithm.


RoadTrack: Realtime Tracking of Road Agents in Dense and Heterogeneous Environments

1 code implementation25 Jun 2019 Rohan Chandra, Uttaran Bhattacharya, Tanmay Randhavane, Aniket Bera, Dinesh Manocha

We present a realtime tracking algorithm, RoadTrack, to track heterogeneous road-agents in dense traffic videos.


TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions

2 code implementations CVPR 2019 Rohan Chandra, Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha

We evaluate the performance of our prediction algorithm, TraPHic, on the standard datasets and also introduce a new dense, heterogeneous traffic dataset corresponding to urban Asian videos and agent trajectories.


Cannot find the paper you are looking for? You can Submit a new open access paper.