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Jeya Maria Jose Valanarasu

7 accepted papers

2026

Masked-Diffusion Autoencoders for 3D Medical Vision Representation Learning

CVPR 2026

Effective medical image analysis requires representations that capture both global anatomical structure and fine-grained tissue texture. Current self-supervised approaches exhibit limited capacity to address both requirements simultaneously. Invariance-based methods learn through augmentation consis

Cited by 0SourceScholar
2025

Time-to-Event Pretraining for 3D Medical Imaging

ICLR 2025poster

With the rise of medical foundation models and the growing availability of imaging data, scalable pretraining techniques offer a promising way to identify imaging biomarkers predictive of future disease risk. While current self-supervised methods for 3D medical imaging models capture local structura…

2024

MaxFusion: Plug&Play Multi-Modal Generation in Text-to-Image Diffusion Models

ECCV 2024poster

"Large diffusion-based Text-to-Image (T2I) models have shown impressive generative powers for text-to-image generation and spatially conditioned image generation. We can train the model end-to-end with paired data for most applications to obtain photorealistic generation quality. However, to add a t…

Cited by 10SourcePDFScholar
2023

Ambiguous Medical Image Segmentation Using Diffusion Models

CVPR 2023poster

Collective insights from a group of experts have always proven to outperform an individual's best diagnostic for clinical tasks. For the task of medical image segmentation, existing research on AI-based alternatives focuses more on developing models that can imitate the best individual rather than h…

2023

Interactive Portrait Harmonization

ICLR 2023poster

Current image harmonization methods consider the entire background as the guidance for harmonization. However, this may limit the capability for user to choose any specific object/person in the background to guide the harmonization. To enable flexible interaction between user and harmonization, we i…

Cited by 8SourcePDFScholar
2022

SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving

ICRA 2022poster

Road extraction is an essential step in building autonomous navigation systems. Detecting road segments is challenging as they are of varying widths, bifurcated throughout the image, and are often occluded by terrain, cloud, or other weather conditions. Using just convolution neural networks (ConvNe…

Cited by 50SourcecodeScholar
2022

TransWeather: Transformer-Based Restoration of Images Degraded by Adverse Weather Conditions

CVPR 2022poster

Removing adverse weather conditions like rain, fog, and snow from images is an important problem in many applications. Most methods proposed in the literature have been designed to deal with just removing one type of degradation. Recently, a CNN-based method using neural architecture search (All-in-…

Cited by 398PDFcodeScholar