U-kan makes strong backbone for medical image segmentation and generation
U-Net has become a cornerstone in various visual applications such as image segmentation
and diffusion probability models. While numerous innovative designs and improvements …
and diffusion probability models. While numerous innovative designs and improvements …
Endora: Video Generation Models as Endoscopy Simulators
Generative models hold promise for revolutionizing medical education, robot-assisted
surgery, and data augmentation for machine learning. Despite progress in generating 2D …
surgery, and data augmentation for machine learning. Despite progress in generating 2D …
Steganerf: Embedding invisible information within neural radiance fields
Recent advancements in neural rendering have paved the way for a future marked by the
widespread distribution of visual data through the sharing of Neural Radiance Field (NeRF) …
widespread distribution of visual data through the sharing of Neural Radiance Field (NeRF) …
Gtp-4o: Modality-prompted heterogeneous graph learning for omni-modal biomedical representation
Recent advances in learning multi-modal representation have witnessed the success in
biomedical domains. While established techniques enable handling multi-modal …
biomedical domains. While established techniques enable handling multi-modal …
EndoSparse: Real-Time Sparse View Synthesis of Endoscopic Scenes using Gaussian Splatting
Abstract 3D reconstruction of biological tissues from a collection of endoscopic images is a
key to unlock various important downstream surgical applications with 3D capabilities …
key to unlock various important downstream surgical applications with 3D capabilities …
Gaussianstego: A generalizable stenography pipeline for generative 3d gaussians splatting
Recent advancements in large generative models and real-time neural rendering using
point-based techniques pave the way for a future of widespread visual data distribution …
point-based techniques pave the way for a future of widespread visual data distribution …
Domain generalization on medical imaging classification using episodic training with task augmentation
Medical imaging datasets usually exhibit domain shift due to the variations of scanner
vendors, imaging protocols, etc. This raises the concern about the generalization capacity of …
vendors, imaging protocols, etc. This raises the concern about the generalization capacity of …
CLIFF: Continual Latent Diffusion for Open-Vocabulary Object Detection
Open-vocabulary object detection (OVD) utilizes imagelevel cues to expand the linguistic
space of region proposals, thereby facilitating the detection of diverse novel classes. Recent …
space of region proposals, thereby facilitating the detection of diverse novel classes. Recent …
Diffrect: Latent diffusion label rectification for semi-supervised medical image segmentation
Semi-supervised medical image segmentation aims to leverage limited annotated data and
rich unlabeled data to perform accurate segmentation. However, existing semi-supervised …
rich unlabeled data to perform accurate segmentation. However, existing semi-supervised …
Learning to estimate 6dof pose from limited data: A few-shot, generalizable approach using rgb images
The accurate estimation of six degrees-of-freedom (6DoF) object poses is essential for many
applications in robotics and augmented reality. However, existing methods for 6DoF pose …
applications in robotics and augmented reality. However, existing methods for 6DoF pose …