◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Liang Ma

7 papers hereh-index 4346 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author7

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • cs.AI1
same name
  • Liang Ma — 28 papers, h 12
  • Liang Ma — 23 papers, h 16
  • Liang Ma — 19 papers, h 22
  • Liang Ma — 9 papers, h 3
  • Liang Ma — 6 papers, h 4
  • Liang Ma — 5 papers, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182025
most citedForward Compatible Few-Shot Class-Incremental Learning

15 citations · 21 across the 7 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022★ 1 cited

2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach

Yilu Guo, Shicai Yang, Weijie Chen +3

Convolutional neural networks (CNNs) have achieved significant success in image classification by utilizing large-scale datasets. However, it is still of great challenge to learn f…

cs.CV2022

Self-distilled Knowledge Delegator for Exemplar-free Class Incremental Learning

Fanfan Ye, Liang Ma, Qiaoyong Zhong +2

Exemplar-free incremental learning is extremely challenging due to inaccessibility of data from old tasks. In this paper, we attempt to exploit the knowledge encoded in a previousl…

cs.CV2022★ 15 cited

Forward Compatible Few-Shot Class-Incremental Learning

Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye +3

Novel classes frequently arise in our dynamically changing world, e.g., new users in the authentication system, and a machine learning model should recognize new classes without fo…

cs.CV2022★ 3 cited

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks

Da-Wei Zhou, Han-Jia Ye, Liang Ma +3

New classes arise frequently in our ever-changing world, e.g., emerging topics in social media and new types of products in e-commerce. A model should recognize new classes and mea…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.