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20182024
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cs.CV2024

PreciseControl: Enhancing Text-To-Image Diffusion Models with Fine-Grained Attribute Control

Rishubh Parihar, Sachidanand VS, Sabariswaran Mani +2

Recently, we have seen a surge of personalization methods for text-to-image (T2I) diffusion models to learn a concept using a few images. Existing approaches, when used for face pe…

cs.CV2023

Exploring Attribute Variations in Style-based GANs using Diffusion Models

Rishubh Parihar, Prasanna Balaji, Raghav Magazine +4

Existing attribute editing methods treat semantic attributes as binary, resulting in a single edit per attribute. However, attributes such as eyeglasses, smiles, or hairstyles exhi…

cs.CV20233 cited

NoisyTwins: Class-Consistent and Diverse Image Generation through StyleGANs

Harsh Rangwani, Lavish Bansal, Kartik Sharma +3

StyleGANs are at the forefront of controllable image generation as they produce a latent space that is semantically disentangled, making it suitable for image editing and manipulat…

cs.CV2022

LEAD: Self-Supervised Landmark Estimation by Aligning Distributions of Feature Similarity

Tejan Karmali, Abhinav Atrishi, Sai Sree Harsha +3

In this work, we introduce LEAD, an approach to discover landmarks from an unannotated collection of category-specific images. Existing works in self-supervised landmark detection…

cs.CV2021

Deep Implicit Surface Point Prediction Networks

Rahul Venkatesh, Tejan Karmali, Sarthak Sharma +4

Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit repr…