7 papers
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…
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…
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…
Gazing at Rewards: Eye Movements as a Lens into Human and AI Decision-Making in Hybrid Visual Foraging
Bo Wang, Dingwei Tan, Yen-Ling Kuo +4
Imagine searching a collection of coins for quarters (), dimes (), nickels (), and pennies ()-a hybrid foraging task where observers look for multiple insta…
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…
Pose Prior Learner: Unsupervised Categorical Prior Learning for Pose Estimation
Ziyu Wang, Shuangpeng Han, Mengmi Zhang
A prior represents a set of beliefs or assumptions about a system, aiding inference and decision-making. In this paper, we introduce the challenge of unsupervised categorical prior…