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cs.CV2026

PRISM: Progressive Reasoning through Iterative Slot Memory for Vision

Ziyu Wang, Shuangpeng Han, Mengmi Zhang

Modern vision models process images in a single feed-forward pass, which limits their ability to recover missing evidence or refine uncertain representations under incomplete obser…

cs.CV2026

Learning to Perceive "Where": Spatial Pretext Tasks for Robust Self-Supervised Learning

Yang Shen, Yusen Cai, Weronika Hryniewska-Guzik +2

Existing self-supervised learning (SSL) methods primarily learn object-invariant representations but often neglect the spatial structure and relationships among object parts. To ad…

cs.CV2025

Learning to See Through a Baby's Eyes: Early Visual Diets Enable Robust Visual Intelligence in Humans and Machines

Yusen Cai, Qing Lin, Bhargava Satya Nunna +1

Newborns perceive the world with low-acuity, color-degraded, and temporally continuous vision, which gradually sharpens as infants develop. To explore the ecological advantages of…

cs.CV2025

Peering into the Unknown: Active View Selection with Neural Uncertainty Maps for 3D Reconstruction

Zhengquan Zhang, Feng Xu, Mengmi Zhang

Some perspectives naturally provide more information than others. How can an AI system determine which viewpoint offers the most valuable insight for accurate and efficient 3D obje…

cs.CV2024

Unforgettable Lessons from Forgettable Images: Intra-Class Memorability Matters in Computer Vision

Jie Jing, Yongjian Huang, Serena J. -W. Wang +5

We introduce intra-class memorability, where certain images within the same class are more memorable than others despite shared category characteristics. To investigate what featur…

cs.CV2024

Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases

Cristian Meo, Akihiro Nakano, Mircea Lică +7

Unsupervised object-centric learning from videos is a promising approach towards learning compositional representations that can be applied to various downstream tasks, such as pre…