activity
20152023
most citedA continual learning survey: Defying forgetting in classification tasks

1.7k citations · 3.2k across the 31 of their papers we have counts for

collaborators
Showing 2020Show all

5 papers · 1 filter

eess.IV2020★ 63 cited

Revisiting Temporal Modeling for Video Super-resolution

Takashi Isobe, Fang Zhu, Xu Jia +1

Video super-resolution plays an important role in surveillance video analysis and ultra-high-definition video display, which has drawn much attention in both the research and indus…

cs.CV2020★ 15 cited

Video Super-Resolution with Recurrent Structure-Detail Network

Takashi Isobe, Xu Jia, Shuhang Gu +3

Most video super-resolution methods super-resolve a single reference frame with the help of neighboring frames in a temporal sliding window. They are less efficient compared to the…

cs.CV2020★ 9 cited

Video Super-resolution with Temporal Group Attention

Takashi Isobe, Songjiang Li, Xu Jia +6

Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we pro…

cs.CV2020★ 2 cited

Learning to Select Base Classes for Few-shot Classification

Linjun Zhou, Peng Cui, Xu Jia +2

Few-shot learning has attracted intensive research attention in recent years. Many methods have been proposed to generalize a model learned from provided base classes to novel clas…

cs.CV2020★ 1 cited

Unsupervised Model Personalization while Preserving Privacy and Scalability: An Open Problem

Matthias De Lange, Xu Jia, Sarah Parisot +3

This work investigates the task of unsupervised model personalization, adapted to continually evolving, unlabeled local user images. We consider the practical scenario where a high…