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Learning Disentangled Representation in Object-Centric Models for Visual
  Dynamics Prediction via Transformers

Learning Disentangled Representation in Object-Centric Models for Visual Dynamics Prediction via Transformers

3 July 2024
Sanket Gandhi
Atul
Samanyu Mahajan
Vishal Sharma
Rushil Gupta
Arnab Kumar Mondal
Parag Singla
    ViT
    OCL
ArXivPDFHTML

Papers citing "Learning Disentangled Representation in Object-Centric Models for Visual Dynamics Prediction via Transformers"

12 / 12 papers shown
Title
SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models
SlotDiffusion: Object-Centric Generative Modeling with Diffusion Models
Ziyi Wu
Jingyu Hu
Wuyue Lu
Igor Gilitschenski
Animesh Garg
DiffM
OCL
56
47
0
18 May 2023
Conditional Object-Centric Learning from Video
Conditional Object-Centric Learning from Video
Thomas Kipf
Gamaleldin F. Elsayed
Aravindh Mahendran
Austin Stone
S. Sabour
G. Heigold
Rico Jonschkowski
Alexey Dosovitskiy
Klaus Greff
OCL
76
216
0
24 Nov 2021
Learning Long-term Visual Dynamics with Region Proposal Interaction
  Networks
Learning Long-term Visual Dynamics with Region Proposal Interaction Networks
Haozhi Qi
Xiaolong Wang
Deepak Pathak
Yi-An Ma
Jitendra Malik
55
59
0
05 Aug 2020
Object-Centric Learning with Slot Attention
Object-Centric Learning with Slot Attention
Francesco Locatello
Dirk Weissenborn
Thomas Unterthiner
Aravindh Mahendran
G. Heigold
Jakob Uszkoreit
Alexey Dosovitskiy
Thomas Kipf
OCL
185
832
0
26 Jun 2020
CLEVRER: CoLlision Events for Video REpresentation and Reasoning
CLEVRER: CoLlision Events for Video REpresentation and Reasoning
Kexin Yi
Yuta Saito
Yunzhu Li
Pushmeet Kohli
Jiajun Wu
Antonio Torralba
J. Tenenbaum
NAI
78
465
0
03 Oct 2019
How Powerful are Graph Neural Networks?
How Powerful are Graph Neural Networks?
Keyulu Xu
Weihua Hu
J. Leskovec
Stefanie Jegelka
GNN
175
7,554
0
01 Oct 2018
Relational Neural Expectation Maximization: Unsupervised Discovery of
  Objects and their Interactions
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
Sjoerd van Steenkiste
Michael Chang
Klaus Greff
Jürgen Schmidhuber
BDL
OCL
DRL
131
290
0
28 Feb 2018
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
Eli Shechtman
Oliver Wang
EGVM
299
11,610
0
11 Jan 2018
Graph Attention Networks
Graph Attention Networks
Petar Velickovic
Guillem Cucurull
Arantxa Casanova
Adriana Romero
Pietro Lio
Yoshua Bengio
GNN
345
19,991
0
30 Oct 2017
A Compositional Object-Based Approach to Learning Physical Dynamics
A Compositional Object-Based Approach to Learning Physical Dynamics
Michael Chang
T. Ullman
Antonio Torralba
J. Tenenbaum
AI4CE
OCL
331
439
0
01 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics
Interaction Networks for Learning about Objects, Relations and Physics
Peter W. Battaglia
Razvan Pascanu
Matthew Lai
Danilo Jimenez Rezende
Koray Kavukcuoglu
AI4CE
OCL
PINN
GNN
457
1,405
0
01 Dec 2016
Semi-Supervised Classification with Graph Convolutional Networks
Semi-Supervised Classification with Graph Convolutional Networks
Thomas Kipf
Max Welling
GNN
SSL
485
28,901
0
09 Sep 2016
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