iSEE: Object Permanence Through Self-Supervision

arXiv:2610.01201 · cs.CV · Submitted 2026-10-01 · Read on arXiv

cs.CV

Submitted: 2026-10-01

Updated: 2026-10-01

Terminology

• In International Conference on Learning Representations — 10× in this paper
• World Model — 7× in this paper · explained in 7 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 4× in this paper
• Temporal Evidence Normalisation — 4× in this paper
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Representation Learning — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• In European Conference on Computer Vision — 2× in this paper
• In International Conference on Machine Learning — 2× in this paper
• Robustness — 2× in this paper · explained in 5 episodes
• Action-Conditioned Dynamics — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Amodal Completion — 1× in this paper · explained in 1 episode
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Decode — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Latent Dynamics — 1× in this paper · explained in 2 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Stochastic Dynamics — 1× in this paper · explained in 2 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Temporal consistency — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames
• DDLP: Unsupervised Object-Centric Video Prediction with Deep Dynamic Latent Particles
• Latent Particle World Models: Self-supervised Object-centric Stochastic Dynamics Modeling
• Slot State Space Models
• Reasoning-Enhanced Object-Centric Learning for Videos
• Selective Synergistic Learning for Video Object-Centric Learning
• TSA: Temporal Slot Activation for Persistent Object-Centric Video Representation
• What DINO saw: ALiBi positional encoding reduces positional bias in Vision Transformers
• OCK: Unsupervised Dynamic Video Prediction with Object-Centric Kinematics
• Learning Object Permanence from Videos via Latent Imaginations
• PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning
• Rethinking Object-Centric Representations for Video Dynamics Modeling

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