Enis Simsar

Orcid: 0000-0002-6662-3249

According to our database1, Enis Simsar authored at least 14 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
CLoRA: A Contrastive Approach to Compose Multiple LoRA Models.
CoRR, 2024

A foundation model utilizing chest CT volumes and radiology reports for supervised-level zero-shot detection of abnormalities.
CoRR, 2024

2023
LIME: Localized Image Editing via Attention Regularization in Diffusion Models.
CoRR, 2023

CONFORM: Contrast is All You Need For High-Fidelity Text-to-Image Diffusion Models.
CoRR, 2023

DENTEX: An Abnormal Tooth Detection with Dental Enumeration and Diagnosis Benchmark for Panoramic X-rays.
CoRR, 2023

GenerateCT: Text-Guided 3D Chest CT Generation.
CoRR, 2023

Fantastic Style Channels and Where to Find Them: A Submodular Framework for Discovering Diverse Directions in GANs.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Diffusion-Based Hierarchical Multi-label Object Detection to Analyze Panoramic Dental X-Rays.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

LatentSwap3D: Semantic Edits on 3D Image GANs.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Object-Aware Monocular Depth Prediction With Instance Convolutions.
IEEE Robotics Autom. Lett., 2022

Rank in Style: A Ranking-based Approach to Find Interpretable Directions.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
Graph2Pix: A Graph-Based Image to Image Translation Framework.
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

LatentCLR: A Contrastive Learning Approach for Unsupervised Discovery of Interpretable Directions.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2019
Comparison of Deep Generative Models for the Generation of Handwritten Character Images.
Proceedings of the 27th Signal Processing and Communications Applications Conference, 2019


  Loading...