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Found 24 papers, 12 papers with code
Cosmos World Foundation Model Platform for Physical AI
We position a world foundation model as a general-purpose world model that can be fine-tuned into customized world models for downstream applications.
Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models
We introduce Edify Image, a family of diffusion models capable of generating photorealistic image content with pixel-perfect accuracy.
HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion
Additionally, we train a warping module to align the hair color with the target region.
One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation
Diffusion models, praised for their success in generative tasks, are increasingly being applied to robotics, demonstrating exceptional performance in behavior cloning.
JeDi: Joint-Image Diffusion Models for Finetuning-Free Personalized Text-to-Image Generation
Personalized text-to-image generation models enable users to create images that depict their individual possessions in diverse scenes, finding applications in various domains.
Holo-Relighting: Controllable Volumetric Portrait Relighting from a Single Image
At the core of portrait photography is the search for ideal lighting and viewpoint.
Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesions
On one hand, this "one-image-one-network" learning ensures complete patient privacy as it does not use any images from other patients as the training data.
Securing Deep Generative Models with Universal Adversarial Signature
Prior research attempted to mitigate these threats by detecting generated images, but the varying traces left by different generative models make it challenging to create a universal detector capable of generalizing to new, unseen generative models.
SceneComposer: Any-Level Semantic Image Synthesis
We propose a new framework for conditional image synthesis from semantic layouts of any precision levels, ranging from pure text to a 2D semantic canvas with precise shapes.
Shape-guided Object Inpainting
Therefore, we propose a new data preparation method and a novel Contextual Object Generator (CogNet) for the object inpainting task.
SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches
Our model can be trained in a self-supervised fashion by learning the reconstruction of an image region from the style vector and sketch.
Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence
Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses.
CR-Fill: Generative Image Inpainting With Auxiliary Contextual Reconstruction
The auxiliary branch (i. e. CR loss) is required only during training, and only the inpainting generator is required during the inference.
Ranked #10 on
Image Inpainting
on Places2
CR-Fill: Generative Image Inpainting with Auxiliary Contexutal Reconstruction
Due to the lack of supervision signals for the correspondence between missing regions and known regions, it may fail to find proper reference features, which often leads to artifacts in the results.
High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling
To address this challenge, we propose an iterative inpainting method with a feedback mechanism.
Ranked #8 on
Image Inpainting
on Places2
Delay Adaptation Method for Relay Assisted Optical Wireless Systems
In this paper, we investigate optical wireless repeaters as relay terminals between a transmitter and a user in an Infrared Optical Wireless Communication (IROWC) system.
Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation
SSNet consists of a segmentation network (SN) and a saliency aggregation module (SAM).
Multi-source weak supervision for saliency detection
To this end, we propose a unified framework to train saliency detection models with diverse weak supervision sources.
Automatic Seismic Salt Interpretation with Deep Convolutional Neural Networks
One of the most crucial tasks in seismic reflection imaging is to identify the salt bodies with high precision.
Application of Machine Learning in Rock Facies Classification with Physics-Motivated Feature Augmentation
This paper shows the inclusion of physics-motivated feature interaction in feature augmentation can further improve the capability of machine learning in rock facies classification.
Learning to Promote Saliency Detectors
The categories and appearance of salient objects vary from image to image, therefore, saliency detection is an image-specific task.
Scalable Mutual Information Estimation using Dependence Graphs
To the best of our knowledge EDGE is the first non-parametric MI estimator that can achieve parametric MSE rates with linear time complexity.
Statistics of Deep Generated Images
Here, we explore the low-level statistics of images generated by state-of-the-art deep generative models.
An Unsupervised Game-Theoretic Approach to Saliency Detection
Saliency maps are generated according to each region's strategy in the Nash equilibrium of the proposed Saliency Game.
