7 citations · 9 across the 7 of their papers we have counts for
11 papers
SCOT: Self-Supervised Contrastive Pretraining For Zero-Shot Compositional Retrieval
Bhavin Jawade, Joao V. B. Soares, Kapil Thadani +6
Compositional image retrieval (CIR) is a multimodal learning task where a model combines a query image with a user-provided text modification to retrieve a target image. CIR finds…
Salient Object-Aware Background Generation using Text-Guided Diffusion Models
Amir Erfan Eshratifar, Joao V. B. Soares, Kapil Thadani +4
Generating background scenes for salient objects plays a crucial role across various domains including creative design and e-commerce, as it enhances the presentation and context o…
Efficient Training of Deep Convolutional Neural Networks by Augmentation in Embedding Space
Mohammad Saeed Abrishami, Amir Erfan Eshratifar, David Eigen +3
Recent advances in the field of artificial intelligence have been made possible by deep neural networks. In applications where data are scarce, transfer learning and data augmentat…
Runtime Deep Model Multiplexing for Reduced Latency and Energy Consumption Inference
Amir Erfan Eshratifar, Massoud Pedram
We propose a learning algorithm to design a light-weight neural multiplexer that given the input and computational resource requirements, calls the model that will consume the mini…
Video Person Re-ID: Fantastic Techniques and Where to Find Them
Priyank Pathak, Amir Erfan Eshratifar, Michael Gormish
The ability to identify the same person from multiple camera views without the explicit use of facial recognition is receiving commercial and academic interest. The current status-…
Coarse2Fine: A Two-stage Training Method for Fine-grained Visual Classification
Amir Erfan Eshratifar, David Eigen, Michael Gormish +1
Small inter-class and large intra-class variations are the main challenges in fine-grained visual classification. Objects from different classes share visually similar structures a…