Multimodal image synthesis and editing: A survey and taxonomy
As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …
among multimodal information plays a key role for the creation and perception of multimodal …
A review of recurrent neural networks: LSTM cells and network architectures
Y Yu, X Si, C Hu, J Zhang - Neural computation, 2019 - direct.mit.edu
Recurrent neural networks (RNNs) have been widely adopted in research areas concerned
with sequential data, such as text, audio, and video. However, RNNs consisting of sigma …
with sequential data, such as text, audio, and video. However, RNNs consisting of sigma …
Stylegan-human: A data-centric odyssey of human generation
Unconditional human image generation is an important task in vision and graphics, enabling
various applications in the creative industry. Existing studies in this field mainly focus on …
various applications in the creative industry. Existing studies in this field mainly focus on …
Tech: Text-guided reconstruction of lifelike clothed humans
Y Huang, H Yi, Y ** network
Instance-level human parsing towards real-world human analysis scenarios is still under-
explored due to the absence of sufficient data resources and technical difficulty in parsing …
explored due to the absence of sufficient data resources and technical difficulty in parsing …
Look into person: Joint body parsing & pose estimation network and a new benchmark
Human parsing and pose estimation have recently received considerable interest due to
their substantial application potentials. However, the existing datasets have limited numbers …
their substantial application potentials. However, the existing datasets have limited numbers …
Look into person: Self-supervised structure-sensitive learning and a new benchmark for human parsing
Human parsing has recently attracted a lot of research interests due to its huge application
potentials. However existing datasets have limited number of images and annotations, and …
potentials. However existing datasets have limited number of images and annotations, and …
Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound
In this work we propose a novel approach to perform segmentation by leveraging the
abstraction capabilities of convolutional neural networks (CNNs). Our method is based on …
abstraction capabilities of convolutional neural networks (CNNs). Our method is based on …