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SelfEval: Leveraging the discriminative nature of generative models for evaluation.
Under Submission
Repurpose generative models as discriminative models to evaluate generative performance.
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Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioning.
Under Submission
State-of-the-art Diffusion-based Text-to-Video generation method.
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InstanceDiffusion: Instance-level Control for Image Generation.
CVPR, 2024
A novel and effective method to enable precise instance-level control for text-to-image generation.
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MOST: Multiple Object localization with Self-supervised Transformers for object discovery.
ICCV, 2023 (Oral Presentation)
Localize multiple objects in a real world images in an unsupervised fashion without any training using Self-supervised Transformers.
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SparseDet: Improving Sparsely Annotated Object Detection with Pseudo-positive Mining.
ICCV, 2023
Improve performance of detectors trained using missing annotations by posing the problem as region-based semi-supervised learning.
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The Pursuit of Knowledge: Discovering and Localizing new concepts using Dual Memory
ICCV, 2021
Equip machines with capabilities to automatically discover and learn models for new categories from a large unlabeled dataset.
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Towards Discovery and Attribution of Open-world GAN Generated Images.
ICCV, 2021
Automatically discover and attribute open-world GAN images.
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Self-Denoising neural networks for few shot learning
Novel architecture based on denoising auto-encoders to improve few shot learning.
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An Empirical analysis of Boosting Deep Networks
IJCNN, 2022
Empirical evidence that a single large neural network is usually more accurate than a boosted ensemble of neural networks with the same number of total parameters
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Towards Accurate Visual and Natural language-based vehicle retrieval systems.
NVIDIA AI City Challenge, CVPR Workshops, 2021
Proposed a real-time system for image-based vehicle re-identification and natural language-based vehicle retrieval.
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Towards Real-Time Systems for Vehicle Re-Identification, Multi-Camera Tracking, and Anomaly Detection.
NVIDIA AI City Challenge, CVPR Workshops, 2020
Proposed a Real-Time system for Vehicle Re-identification, Multi-Camera Tracking, and Anomaly Detection in a network of traffic cameras.
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Detecting Human-Object Interactions via Functional Generalization.
AAAI, 2020
Humans interact with functionally similar objects in a similar manner.
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Spatial Priming for Detecting Human-Object Interactions
arxiv
A method for exploiting the spatial layout information of a human and an object for detecting HOIs in images.
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A Dual-Path Model With Adaptive Attention for Vehicle Re-Identification
ICCV, 2019 (Oral Presentation)
Proposed a novel dual-path adaptive attention model for Vehicle re-identification.
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Body Part Alignment and Temporal Attention Pooling for Video-Based Person ReIdentification
BMVC, 2019
Training deep networks with the ability to align features achieves state of the art performance on Person Re-identification.
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