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Found 17 papers, 9 papers with code
Large Scale Correlation Clustering Optimization
This analogy allows us to suggest several new optimization algorithms, which exploit the intrinsic "model-selection" capability of the functional to automatically recover the underlying number of clusters.
InGAN: Capturing and Remapping the "DNA" of a Natural Image
In this paper we propose an "Internal GAN" (InGAN) - an image-specific GAN - which trains on a single input image and learns its internal distribution of patches.
Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal Learning
In particular, the higher spatial resolution of video frames provides strong examples as to how to increase the temporal resolution of that video.
Point of Care Image Analysis for COVID-19
Collaborating with several hospitals in Israel we collect a large dataset of CXRs and use this dataset to train a neural network obtaining above 90% detection rate for COVID-19.
Segmenting Microcalcifications in Mammograms and its Applications
Microcalcifications are small deposits of calcium that appear in mammograms as bright white specks on the soft tissue background of the breast.
Drop the GAN: In Defense of Patches Nearest Neighbors as Single Image Generative Models
Recently, however, Single Image GANs were introduced both as a superior solution for such manipulation tasks, but also for remarkable novel generative tasks.
Diverse Generation from a Single Video Made Possible
GANs are able to perform generation and manipulation tasks, trained on a single video.
Deep ViT Features as Dense Visual Descriptors
To distill the power of ViT features from convoluted design choices, we restrict ourselves to lightweight zero-shot methodologies (e. g., binning and clustering) applied directly to the features.
Ranked #6 on
Feature Upsampling
on ImageNet
Splicing ViT Features for Semantic Appearance Transfer
Specifically, our goal is to generate an image in which objects in a source structure image are "painted" with the visual appearance of their semantically related objects in a target appearance image.
Diverse Video Generation from a Single Video
GANs are able to perform generation and manipulation tasks, trained on a single video.
Combining Internal and External Constraints for Unrolling Shutter in Videos
This allows to constrain the GS output video using video-specific constraints imposed by the RS input video.
Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation
Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts.
Ranked #10 on
Text-based Image Editing
on PIE-Bench
DeepCut: Unsupervised Segmentation using Graph Neural Networks Clustering
This direct connection between the raw features and the clustering objective enables us to implicitly perform classification of the clusters between different graphs, resulting in part semantic segmentation without the need for additional post-processing steps.
Ranked #1 on
Unsupervised Object Localization
on COCO_20k
Detecting Bone Lesions in X-Ray Under Diverse Acquisition Conditions
The diagnosis of primary bone tumors is challenging, as the initial complaints are often non-specific.
TokenFlow: Consistent Diffusion Features for Consistent Video Editing
In this work, we present a framework that harnesses the power of a text-to-image diffusion model for the task of text-driven video editing.
Disentangling Structure and Appearance in ViT Feature Space
Specifically, our goal is to generate an image in which objects in a source structure image are "painted" with the visual appearance of their semantically related objects in a target appearance image.
DINO-Tracker: Taming DINO for Self-Supervised Point Tracking in a Single Video
Specifically, our framework simultaneously adopts DINO's features to fit to the motion observations of the test video, while training a tracker that directly leverages the refined features.
