
The author argues that by using prediction as the main learning objective, a novel network architecture called OPPLE can simultaneously learn object segmentation, depth perception, and 3D object localization without supervision. This approach is inspired by how infants develop perceptual abilities.


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learning-3d-object-centric-representation-through-prediction


Learning 3D Object-Centric Representation Through Prediction


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Objects are learned through prediction, mimicking human infant abilities.


3d-object-centric-representation-learning-through-prediction


3D Object-Centric Representation Learning Through Prediction



A simple, scalable, and non-iterative method called SAMP (Simplified Slot Attention with Max Pool Priors) that learns object-centric representations from images by inducing competition and specialization among slots.


simplified-and-scalable-object-centric-representation-learning-with-competitive-slot-extraction


Simplified and Scalable Object-Centric Representation Learning with Competitive Slot Extraction
