4 accepted papers
In this paper, we present DiffuDETR, a novel approach that formulates object detection as a conditional object query generation task, conditioned on the image and a set of noisy reference points. We integrate DETR-based models with denoising diffusion training to generate object queries' reference p…
Image flare is a common problem that occurs when a camera lens is pointed at a strong light source. It can manifest as ghosting, blooming, or other artifacts that can degrade the image quality. We propose a novel deep learning approach for flare removal that uses a combination of depth estimation an…
Low-light images represent an obstacle for computer vision tasks due to the lack of perceptual quality. Also, it is challenging to enhance images and adapt to different illumination conditions. To address this problem, we introduce a zero-shot learning approach. We use a 3-stage model trained withou…
Convolution Neural Networks (CNN) excelled humans in many classification tasks, including medical imaging applications. However, model interpretation is still an active research area. In this paper, we address the model interpretation problem for the Diabetic Retinopathy grading task. We propose a n…