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Found 17 papers, 4 papers with code
FrameNeRF: A Simple and Efficient Framework for Few-shot Novel View Synthesis
We present a novel framework, called FrameNeRF, designed to apply off-the-shelf fast high-fidelity NeRF models with fast training speed and high rendering quality for few-shot novel view synthesis tasks.
RadOcc: Learning Cross-Modality Occupancy Knowledge through Rendering Assisted Distillation
3D occupancy prediction is an emerging task that aims to estimate the occupancy states and semantics of 3D scenes using multi-view images.
FedEdge AI-TC: A Semi-supervised Traffic Classification Method based on Trusted Federated Deep Learning for Mobile Edge Computing
The framework enhances user privacy and model credibility, offering a comprehensive solution for dependable and transparent Network TC in 5G CPE, thus enhancing service quality and security.
Contrast-augmented Diffusion Model with Fine-grained Sequence Alignment for Markup-to-Image Generation
The recently rising markup-to-image generation poses greater challenges as compared to natural image generation, due to its low tolerance for errors as well as the complex sequence and context correlations between markup and rendered image.
Multi-scale multi-modal micro-expression recognition algorithm based on transformer
A micro-expression is a spontaneous unconscious facial muscle movement that can reveal the true emotions people attempt to hide.
Reconstruction of compressed spectral imaging based on global structure and spectral correlation
To take full exploration of the constraints between spectra, the coefficients corresponding to the convolution kernel are constrained by the L_(2, 1)norm to improve spectral accuracy.
Implicit and Efficient Point Cloud Completion for 3D Single Object Tracking
The point cloud based 3D single object tracking has drawn increasing attention.
A Semantic Consistency Feature Alignment Object Detection Model Based on Mixed-Class Distribution Metrics
Then, a Semantic Consistency Feature Alignment Model (SCFAM) based on mixed-classes $H-divergence$ was also presented.
Product semantics translation from brain activity via adversarial learning
To modify a design semantic of a given product from personalised brain activity via adversarial learning, in this work, we propose a deep generative transformation model to modify product semantics from the brain signal.
Verifying Design through Generative Visualization of Neural Activities
A recurrent neural network is used as the encoder to learn latent representation from electroencephalogram (EEG) signals, recorded while subjects looked at 50 categories of images.
A General Framework for Revealing Human Mind with auto-encoding GANs
For this reason, we propose an end-to-end brain decoding framework which translates brain activity into an image by latent space alignment.
Implicit Subspace Prior Learning for Dual-Blind Face Restoration
Face restoration is an inherently ill-posed problem, where additional prior constraints are typically considered crucial for mitigating such pathology.
Towards Fine-grained Human Pose Transfer with Detail Replenishing Network
Human pose transfer (HPT) is an emerging research topic with huge potential in fashion design, media production, online advertising and virtual reality.
Region-adaptive Texture Enhancement for Detailed Person Image Synthesis
The ability to produce convincing textural details is essential for the fidelity of synthesized person images.
Ranked #4 on
Pose Transfer
on Deep-Fashion
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
Existing face restoration researches typically relies on either the degradation prior or explicit guidance labels for training, which often results in limited generalization ability over real-world images with heterogeneous degradations and rich background contents.
Generating Persuasive Visual Storylines for Promotional Videos
Video contents have become a critical tool for promoting products in E-commerce.
Generative Creativity: Adversarial Learning for Bionic Design
Bionic design refers to an approach of generative creativity in which a target object (e. g. a floor lamp) is designed to contain features of biological source objects (e. g. flowers), resulting in creative biologically-inspired design.
