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Found 19 papers, 4 papers with code
Sketch3D: Style-Consistent Guidance for Sketch-to-3D Generation
Recently, image-to-3D approaches have achieved significant results with a natural image as input.
Few-shot Shape Recognition by Learning Deep Shape-aware Features
Thirdly, we propose a decoding module to include the supervision of shape masks and edges and align the original and reconstructed shape features, enforcing the learned features to be more shape-aware.
A Deep Neural Network Based Approach to Building Budget-Constrained Models for Big Data Analysis
Deep learning approaches require collection of data on many different input features or variables for accurate model training and prediction.
Unsupervised Visual Defect Detection with Score-Based Generative Model
Thus, we focus on the unsupervised visual defect detection and localization tasks and propose a novel framework based on the recent score-based generative models, which synthesize the real image by iterative denoising through stochastic differential equations (SDEs).
The 5th Recognizing Families in the Wild Data Challenge: Predicting Kinship from Faces
Recognizing Families In the Wild (RFIW), held as a data challenge in conjunction with the 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG), is a large-scale, multi-track visual kinship recognition evaluation.
Discriminative Cross-Domain Feature Learning for Partial Domain Adaptation
Partial domain adaptation aims to adapt knowledge from a larger and more diverse source domain to a smaller target domain with less number of classes, which has attracted appealing attention.
Families In Wild Multimedia: A Multimodal Database for Recognizing Kinship
Thus, to narrow the gap between research and reality and enhance the power of kinship recognition systems, we extend FIW with multimedia (MM) data (i. e., video, audio, and text captions).
Survey on the Analysis and Modeling of Visual Kinship: A Decade in the Making
We review the public resources and data challenges that enabled and inspired many to hone-in on the views of automatic kinship recognition in the visual domain.
Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge
Recognizing Families In the Wild (RFIW): an annual large-scale, multi-track automatic kinship recognition evaluation that supports various visual kin-based problems on scales much higher than ever before.
What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer
Specifically, we propose a two-stage kin-face generation model to predict the appearance of a child given a pair of parents.
Real-time Memory Efficient Large-pose Face Alignment via Deep Evolutionary Network
To accelerate the model, we propose an efficient network structure to accelerate the evolutionary learning process through a factorization strategy.
LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution
To reduce the computation and memory costs, we propose a novel lightweight deep learning module by low-rank pointwise residual (LPR) convolution, called LPRNet.
Learning Robust Data Representation: A Knowledge Flow Perspective
It is always demanding to learn robust visual representation for various learning problems; however, this learning and maintenance process usually suffers from noise, incompleteness or knowledge domain mismatch.
Cost-sensitive Selection of Variables by Ensemble of Model Sequences
Many applications require the collection of data on different variables or measurements over many system performance metrics.
Arc-support Line Segments Revisited: An Efficient and High-quality Ellipse Detection
Over the years many ellipse detection algorithms spring up and are studied broadly, while the critical issue of detecting ellipses accurately and efficiently in real-world images remains a challenge.
Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation
However, existing approaches separate target label optimization and domain-invariant feature learning as different steps.
Low-Rank Embedded Ensemble Semantic Dictionary for Zero-Shot Learning
Zero-shot learning for visual recognition has received much interest in the most recent years.
A Multi-Stream Bi-Directional Recurrent Neural Network for Fine-Grained Action Detection
We present a multi-stream bi-directional recurrent neural network for fine-grained action detection.
Action Recognition In Videos
Fine-Grained Action Detection
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Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks
Motivated by the lack of a single, unified dataset for kinship recognition, we aim to provide a dataset that captivates the interest of the research community.
