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Found 4 papers, 2 papers with code
GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs
Instead of feature pooling, we use group convolutions to exploit underlying structures of the extracted features on the group, resulting in descriptors that are both discriminative and provably invariant to the group of transformations.
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition
Previous approaches for unsupervised object-oriented scene representation learning are either based on spatial-attention or scene-mixture approaches and limited in scalability which is a main obstacle towards modeling real-world scenes.
Learning and Simulation in Generative Structured World Models
The G-SWM not only unifies the key properties of previous models in a principled framework but also achieves two crucial new abilities, multi-modal uncertainty and situated behavior.
Improving Generative Imagination in Object-Centric World Models
Third, a few key abilities for more faithful temporal imagination such as multimodal uncertainty and situation-awareness are missing.
