Search Results for author:
Found 6 papers, 3 papers with code
Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models
We present a method to create interpretable concept sliders that enable precise control over attributes in image generations from diffusion models.
Unified Concept Editing in Diffusion Models
Text-to-image models suffer from various safety issues that may limit their suitability for deployment.
Erasing Concepts from Diffusion Models
We propose a fine-tuning method that can erase a visual concept from a pre-trained diffusion model, given only the name of the style and using negative guidance as a teacher.
DC-Art-GAN: Stable Procedural Content Generation using DC-GANs for Digital Art
In this manuscript, we advocate the concept of using deep generative networks with adversarial training for a stable and variant art generation.
Computer Vision for Autonomous Vehicles
In this work, we try to implement Image Processing techniques in the area of autonomous vehicles, both indoor and outdoor.
How You See Me
Convolution Neural Networks is one of the most powerful tools in the present era of science.
