Learning from few examples: A summary of approaches to few-shot learning
Few-Shot Learning refers to the problem of learning the underlying pattern in the data just
from a few training samples. Requiring a large number of data samples, many deep learning …
from a few training samples. Requiring a large number of data samples, many deep learning …
Deep learning for image colorization: Current and future prospects
Image colorization, as an essential problem in computer vision (CV), has attracted an
increasing amount of researchers attention in recent years, especially deep learning-based …
increasing amount of researchers attention in recent years, especially deep learning-based …
Stargan v2: Diverse image synthesis for multiple domains
A good image-to-image translation model should learn a mapping between different visual
domains while satisfying the following properties: 1) diversity of generated images and 2) …
domains while satisfying the following properties: 1) diversity of generated images and 2) …
Reference-based sketch image colorization using augmented-self reference and dense semantic correspondence
This paper tackles the automatic colorization task of a sketch image given an already-
colored reference image. Colorizing a sketch image is in high demand in comics, animation …
colored reference image. Colorizing a sketch image is in high demand in comics, animation …
Talking-head generation with rhythmic head motion
When people deliver a speech, they naturally move heads, and this rhythmic head motion
conveys prosodic information. However, generating a lip-synced video while moving head …
conveys prosodic information. However, generating a lip-synced video while moving head …
Cross modal retrieval with querybank normalisation
Profiting from large-scale training datasets, advances in neural architecture design and
efficient inference, joint embeddings have become the dominant approach for tackling cross …
efficient inference, joint embeddings have become the dominant approach for tackling cross …
Video-based person re-identification with spatial and temporal memory networks
Video-based person re-identification (reID) aims to retrieve person videos with the same
identity as a query person across multiple cameras. Spatial and temporal distractors in …
identity as a query person across multiple cameras. Spatial and temporal distractors in …
Chromagan: Adversarial picture colorization with semantic class distribution
P Vitoria, L Raad, C Ballester - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
The colorization of grayscale images is an ill-posed problem, with multiple correct solutions.
In this paper, we propose an adversarial learning colorization approach coupled with …
In this paper, we propose an adversarial learning colorization approach coupled with …
Memory oriented transfer learning for semi-supervised image deraining
Deep learning based methods have shown dramatic improvements in image rain removal
by using large-scale paired data of synthetic datasets. However, due to the various …
by using large-scale paired data of synthetic datasets. However, due to the various …
Implicit identity representation conditioned memory compensation network for talking head video generation
Talking head video generation aims to animate a human face in a still image with dynamic
poses and expressions using motion information derived from a target-driving video, while …
poses and expressions using motion information derived from a target-driving video, while …