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Found 21 papers, 6 papers with code
Particularity beyond Commonality: Unpaired Identity Transfer with Multiple References
Unpaired image-to-image translation aims to translate images from the source class to target one by providing sufficient data for these classes.
Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
This work explores the use of 3D generative models to synthesize training data for 3D vision tasks.
Real-time 6K Image Rescaling with Rate-distortion Optimization
Then, an efficient frequency-aware decoder reconstructs a high-fidelity HR image from the LR one in real time.
Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflection
We show that together with a reflection direction-dependent radiance, our model achieves high-quality surface reconstruction on reflective surfaces and outperforms the state-of-the-arts by a large margin.
Contactless Oxygen Monitoring with Gated Transformer
With the increasing popularity of telehealth, it becomes critical to ensure that basic physiological signals can be monitored accurately at home, with minimal patient overhead.
Adaptive Domain Generalization via Online Disagreement Minimization
Domain Generalization (DG) aims to safely transfer a model to unseen target domains by only relying on a set of source domains.
Representation Compensation Networks for Continual Semantic Segmentation
In this work, we study the continual semantic segmentation problem, where the deep neural networks are required to incorporate new classes continually without catastrophic forgetting.
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Image Synthesis via Semantic Composition
In this paper, we present a novel approach to synthesize realistic images based on their semantic layouts.
Delving into Deep Imbalanced Regression
We define Deep Imbalanced Regression (DIR) as learning from such imbalanced data with continuous targets, dealing with potential missing data for certain target values, and generalizing to the entire target range.
Learning Blood Oxygen from Respiration Signals
Further, since breathing can be monitored without body contact by analyzing the radio signal in the environment, we show that oxygen too can be monitored without any wearable devices.
Learning To Know Where To See: A Visibility-Aware Approach for Occluded Person Re-Identification
Several mainstream methods utilize extra cues (e. g., human pose information) to distinguish human parts from obstacles to alleviate the occlusion problem.
Domain Adaptive Image-to-Image Translation
Our framework introduces two sub-modules -- one maps testing samples to the valid input domain of the I2I model, and the other transforms the output of I2I model to expected results.
Attentive Normalization for Conditional Image Generation
Traditional convolution-based generative adversarial networks synthesize images based on hierarchical local operations, where long-range dependency relation is implicitly modeled with a Markov chain.
VCNet: A Robust Approach to Blind Image Inpainting
Blind inpainting is a task to automatically complete visual contents without specifying masks for missing areas in an image.
Semantic Component Decomposition for Face Attribute Manipulation
The model decomposes a facial attribute into multiple semantic components, each corresponds to a specific face region.
Homomorphic Latent Space Interpolation for Unpaired Image-To-Image Translation
We also show that this framework can be applied to multi-domain and multi-modal translation.
Facelet-Bank for Fast Portrait Manipulation
Digital face manipulation has become a popular and fascinating way to touch images with the prevalence of smartphones and social networks.
Makeup-Go: Blind Reversion of Portrait Edit
In this paper, we propose the task of restoring a portrait image from this process.
Convolutional Neural Pyramid for Image Processing
We propose a principled convolutional neural pyramid (CNP) framework for general low-level vision and image processing tasks.
Person Re-Identification by Camera Correlation Aware Feature Augmentation
The challenge of person re-identification (re-id) is to match individual images of the same person captured by different non-overlapping camera views against significant and unknown cross-view feature distortion.
An Enhanced Deep Feature Representation for Person Re-identification
In this paper, we focus on the feature representation and claim that hand-crafted histogram features can be complementary to Convolutional Neural Network (CNN) features.
