activity
20142026
most citedTraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted Interactions

233 citations · 902 across the 70 of their papers we have counts for

collaborators

73 papers

cs.CV2026

FineMoLA: Towards Fine-Grained Motion-Language Alignment from Clip-Level Supervision

Tongyan Wang, Zhengyuan Li, Muhan Lin +5

Text-conditioned human motion generation has made rapid progress with the emergence of large-scale motion--language datasets. However, even datasets with rich long-form description…

cs.CV2026

MIME: Multimodal Interactive Motion Encoder

Addison Zucek, Prerit Gupta, Kamila Kuatova +1

Text-motion representation learning has advanced rapidly, with growing interest in multi person interactions for animation, AR/VR, and embodied AI. These settings require represent…

cs.CV2025

Adversarial Agent Behavior Learning in Autonomous Driving Using Deep Reinforcement Learning

Arjun Srinivasan, Anubhav Paras, Aniket Bera

Existing approaches in reinforcement learning train an agent to learn desired optimal behavior in an environment with rule based surrounding agents. In safety critical applications…

cs.HC2025★ 5 cited

Sensitivity to Redirected Walking Considering Gaze, Posture, and Luminance

Niall L. Williams, Logan C. Stevens, Aniket Bera +1

We study the correlations between redirected walking (RDW) rotation gains and patterns in users' posture and gaze data during locomotion in virtual reality (VR). To do this, we con…

cs.CV2025

SimMotionEdit: Text-Based Human Motion Editing with Motion Similarity Prediction

Zhengyuan Li, Kai Cheng, Anindita Ghosh +3

Text-based 3D human motion editing is a critical yet challenging task in computer vision and graphics. While training-free approaches have been explored, the recent release of the…

cs.LG2024★ 1 cited

Learning Lagrangian Interaction Dynamics with Sampling-Based Model Order Reduction

Hrishikesh Viswanath, Yue Chang, Aleksey Panas +3

Simulating physical systems governed by Lagrangian dynamics often entails solving partial differential equations (PDEs) over high-resolution spatial domains, leading to significant…

cs.CV2024★ 2 cited

Speech2UnifiedExpressions: Synchronous Synthesis of Co-Speech Affective Face and Body Expressions from Affordable Inputs

Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha

We present a multimodal learning-based method to simultaneously synthesize co-speech facial expressions and upper-body gestures for digital characters using RGB video data captured…

cs.RO2024★ 1 cited

MTAC: Hierarchical Reinforcement Learning-based Multi-gait Terrain-adaptive Quadruped Controller

Nishaant Shah, Kshitij Tiwari, Aniket Bera

Urban search and rescue missions require rapid first response to minimize loss of life and damage. Often, such efforts are assisted by humanitarian robots which need to handle dyna…

cs.CV2023

RL Dreams: Policy Gradient Optimization for Score Distillation based 3D Generation

Aradhya N. Mathur, Phu Pham, Aniket Bera +1

3D generation has rapidly accelerated in the past decade owing to the progress in the field of generative modeling. Score Distillation Sampling (SDS) based rendering has improved 3…

cs.RO2023★ 1 cited

MIRACLE: Inverse Reinforcement and Curriculum Learning Model for Human-inspired Mobile Robot Navigation

Nihal Gunukula, Kshitij Tiwari, Aniket Bera

In emergency scenarios, mobile robots must navigate like humans, interpreting stimuli to locate potential victims rapidly without interfering with first responders. Existing social…

cs.RO2023★ 1 cited

DREAM: Decentralized Reinforcement Learning for Exploration and Efficient Energy Management in Multi-Robot Systems

Dipam Patel, Phu Pham, Kshitij Tiwari +1

Resource-constrained robots often suffer from energy inefficiencies, underutilized computational abilities due to inadequate task allocation, and a lack of robustness in dynamic en…

cs.RO2023

Trajectory Prediction for Robot Navigation using Flow-Guided Markov Neural Operator

Rashmi Bhaskara, Hrishikesh Viswanath, Aniket Bera

Predicting pedestrian movements remains a complex and persistent challenge in robot navigation research. We must evaluate several factors to achieve accurate predictions, such as p…

cs.CV2023★ 2 cited

DF-TransFusion: Multimodal Deepfake Detection via Lip-Audio Cross-Attention and Facial Self-Attention

Aaditya Kharel, Manas Paranjape, Aniket Bera

With the rise in manipulated media, deepfake detection has become an imperative task for preserving the authenticity of digital content. In this paper, we present a novel multi-mod…

cs.RO2023★ 2 cited

HEROES: Unreal Engine-based Human and Emergency Robot Operation Education System

Anav Chaudhary, Kshitij Tiwari, Aniket Bera

Training and preparing first responders and humanitarian robots for Mass Casualty Incidents (MCIs) often poses a challenge owing to the lack of realistic and easily accessible test…

cs.RO2023★ 5 cited

Optimizing Crowd-Aware Multi-Agent Path Finding through Local Communication with Graph Neural Networks

Phu Pham, Aniket Bera

Multi-Agent Path Finding (MAPF) in crowded environments presents a challenging problem in motion planning, aiming to find collision-free paths for all agents in the system. MAPF fi…

cs.RO2023

Graph-based Decentralized Task Allocation for Multi-Robot Target Localization

Juntong Peng, Hrishikesh Viswanath, Aniket Bera

We introduce a new graph neural operator-based approach for task allocation in a system of heterogeneous robots composed of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehi…

cs.RO2023★ 3 cited

ARTEMIS: AI-driven Robotic Triage Labeling and Emergency Medical Information System

Revanth Krishna Senthilkumaran, Mridu Prashanth, Hrishikesh Viswanath +3

Mass casualty incidents (MCIs) pose a significant challenge to emergency medical services by overwhelming available resources and personnel. Effective victim assessment is the key…

cs.SD2023

AffectEcho: Speaker Independent and Language-Agnostic Emotion and Affect Transfer for Speech Synthesis

Hrishikesh Viswanath, Aneesh Bhattacharya, Pascal Jutras-Dubé +4

Affect is an emotional characteristic encompassing valence, arousal, and intensity, and is a crucial attribute for enabling authentic conversations. While existing text-to-speech (…

cs.RO2023★ 16 cited

Principles and Guidelines for Evaluating Social Robot Navigation Algorithms

Anthony Francis, Claudia Pérez-D'Arpino, Chengshu Li +28

A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation ha…

cs.CV2023★ 20 cited

AZTR: Aerial Video Action Recognition with Auto Zoom and Temporal Reasoning

Xijun Wang, Ruiqi Xian, Tianrui Guan +4

We propose a novel approach for aerial video action recognition. Our method is designed for videos captured using UAVs and can run on edge or mobile devices. We present a learning-…

cs.RO2023

DroNeRF: Real-time Multi-agent Drone Pose Optimization for Computing Neural Radiance Fields

Dipam Patel, Phu Pham, Aniket Bera

We present a novel optimization algorithm called DroNeRF for the autonomous positioning of monocular camera drones around an object for real-time 3D reconstruction using only a few…

cs.RO2023

SG-LSTM: Social Group LSTM for Robot Navigation Through Dense Crowds

Rashmi Bhaskara, Maurice Chiu, Aniket Bera

With the increasing availability and affordability of personal robots, they will no longer be confined to large corporate warehouses or factories but will instead be expected to op…

cs.SD2023★ 6 cited

DanceAnyWay: Synthesizing Beat-Guided 3D Dances with Randomized Temporal Contrastive Learning

Aneesh Bhattacharya, Manas Paranjape, Uttaran Bhattacharya +1

We present DanceAnyWay, a generative learning method to synthesize beat-guided dances of 3D human characters synchronized with music. Our method learns to disentangle the dance mov…

cs.AI2023★ 2 cited

Neural Operator: Is data all you need to model the world? An insight into the paradigm of data-driven scientific ML

Hrishikesh Viswanath, Md Ashiqur Rahman, Abhijeet Vyas +5

Numerical approximations of partial differential equations (PDEs) are routinely employed to formulate the solution of physics, engineering, and mathematical problems involving func…