Search Results for author:
Found 14 papers, 7 papers with code
WROOM: An Autonomous Driving Approach for Off-Road Navigation
Off-road navigation is a challenging problem both at the planning level to get a smooth trajectory and at the control level to avoid flipping over, hitting obstacles, or getting stuck at a rough patch.
ShapeGrasp: Zero-Shot Task-Oriented Grasping with Large Language Models through Geometric Decomposition
Task-oriented grasping of unfamiliar objects is a necessary skill for robots in dynamic in-home environments.
Knowledge-Guided Short-Context Action Anticipation in Human-Centric Videos
This work focuses on anticipating long-term human actions, particularly using short video segments, which can speed up editing workflows through improved suggestions while fostering creativity by suggesting narratives.
Sample-Efficient Learning of Novel Visual Concepts
Despite the advances made in visual object recognition, state-of-the-art deep learning models struggle to effectively recognize novel objects in a few-shot setting where only a limited number of examples are provided.
Emotionally Enhanced Talking Face Generation
To mitigate this, we build a talking face generation framework conditioned on a categorical emotion to generate videos with appropriate expressions, making them more realistic and convincing.
Ranked #1 on
Talking Face Generation
on CREMA-D
Emotional Talking Faces: Making Videos More Expressive and Realistic
Lip synchronization and talking face generation have gained a specific interest from the research community with the advent and need of digital communication in different fields.
FaIRCoP: Facial Image Retrieval using Contrastive Personalization
Retrieving facial images from attributes plays a vital role in various systems such as face recognition and suspect identification.
Multimodal Research in Vision and Language: A Review of Current and Emerging Trends
Deep Learning and its applications have cascaded impactful research and development with a diverse range of modalities present in the real-world data.
UAV Target Tracking in Urban Environments Using Deep Reinforcement Learning
Persistent target tracking in urban environments using UAV is a difficult task due to the limited field of view, visibility obstruction from obstacles and uncertain target motion.
Robotics Systems and Control Systems and Control
DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors
Disentangling the underlying feature attributes within an image with no prior supervision is a challenging task.
C3VQG: Category Consistent Cyclic Visual Question Generation
In this paper, we try to exploit the different visual cues and concepts in an image to generate questions using a variational autoencoder (VAE) without ground-truth answers.
Disentangling Multiple Features in Video Sequences using Gaussian Processes in Variational Autoencoders
Our experiments show that the combination of the improved representations with the novel loss function enable MGP-VAE to outperform the baselines in video prediction.
Ranked #1 on
Video Prediction
on Colored dSprites
Product of Orthogonal Spheres Parameterization for Disentangled Representation Learning
Learning representations that can disentangle explanatory attributes underlying the data improves interpretabilty as well as provides control on data generation.
Geometry of Deep Generative Models for Disentangled Representations
We use several metrics to compare the properties of latent spaces of disentangled representation models in terms of class separability and curvature of the latent-space.
