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Placing Objects in Context via Inpainting for Out-of-distribution
  Segmentation

Placing Objects in Context via Inpainting for Out-of-distribution Segmentation

26 February 2024
Pau de Jorge
Riccardo Volpi
P. Dokania
Philip H. S. Torr
Grégory Rogez
    DiffM
ArXivPDFHTML

Papers citing "Placing Objects in Context via Inpainting for Out-of-distribution Segmentation"

7 / 7 papers shown
Title
Panoramic Out-of-Distribution Segmentation
Panoramic Out-of-Distribution Segmentation
Mengfei Duan
Kailun Yang
Y. Zhang
Yihong Cao
Fei Teng
Kai Luo
Jiaming Zhang
Zhiyong Li
Shutao Li
50
0
0
06 May 2025
MObI: Multimodal Object Inpainting Using Diffusion Models
MObI: Multimodal Object Inpainting Using Diffusion Models
Alexandru Buburuzan
Anuj Sharma
John Redford
P. Dokania
Romain Mueller
DiffM
83
1
0
06 Jan 2025
Reliability in Semantic Segmentation: Can We Use Synthetic Data?
Reliability in Semantic Segmentation: Can We Use Synthetic Data?
Thibaut Loiseau
Tuan-Hung Vu
Mickaël Chen
Patrick Pérez
Matthieu Cord
UQCV
18
12
0
14 Dec 2023
Palette: Image-to-Image Diffusion Models
Palette: Image-to-Image Diffusion Models
Chitwan Saharia
William Chan
Huiwen Chang
Chris A. Lee
Jonathan Ho
Tim Salimans
David J. Fleet
Mohammad Norouzi
DiffM
VLM
325
1,570
0
10 Nov 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,635
0
05 Dec 2016
Image-to-Image Translation with Conditional Adversarial Networks
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola
Jun-Yan Zhu
Tinghui Zhou
Alexei A. Efros
SSeg
212
19,191
0
21 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,042
0
06 Jun 2015
1