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Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on
  Light-Weighed Backbones and Effective Measurement of Multi-Task Learning
  Challenges by Feature Disentanglement

Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on Light-Weighed Backbones and Effective Measurement of Multi-Task Learning Challenges by Feature Disentanglement

5 February 2024
Dayou Mao
Yuhao Chen
Yifan Wu
Maximilian Gilles
Alexander Wong
    AAML
ArXivPDFHTML

Papers citing "Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on Light-Weighed Backbones and Effective Measurement of Multi-Task Learning Challenges by Feature Disentanglement"

2 / 2 papers shown
Title
Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion
  Modeling
Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling
S. Back
Joosoon Lee
Taewon Kim
Sangjun Noh
Raeyoung Kang
Seongho Bak
Kyoobin Lee
29
67
0
23 Sep 2021
Feature Pyramid Networks for Object Detection
Feature Pyramid Networks for Object Detection
Tsung-Yi Lin
Piotr Dollár
Ross B. Girshick
Kaiming He
Bharath Hariharan
Serge J. Belongie
ObjD
154
3,574
0
09 Dec 2016
1