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Common Principle
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Classroom Contents
Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences
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- 1 Intro
- 2 Collaborators
- 3 Why Object-Centric Learning? Explicit object representation
- 4 Tracking by Detection
- 5 Unsupervised Object-Centric Learning
- 6 Common Principle
- 7 Categorization of Approaches
- 8 VIMON: Attention Network
- 9 VIMON: Next-Frame Prediction
- 10 TBA Tracker Array
- 11 TBA Mid-Level Representation
- 12 TBA Spatial Transformation
- 13 Spatial Mixture Models: OP3
- 14 OP3 Dynamics Network
- 15 CLEAR MOT Metrics
- 16 Datasets
- 17 Results on SpMOT
- 18 How Well Do Models Accumulate Evidence Over Time?
- 19 Dependency of Performance on Number of Objects
- 20 Challenging Cases
- 21 VMDS Challenge Sets
- 22 Out-of-Distribution Test Sets
- 23 Runtime Analysis Runtime on Single RTX 2080 TI GPU
- 24 Conclusions
- 25 2D Annotations
