12 papers
Personalized Emotional Intelligence in Generative AI through Symbolic Affective Reasoning
Qing Lin, Mengmi Zhang
Emotional intelligence enables humans to recognize emotions, infer their causes, reason about interventions, and modify their environment to achieve desired affective states. Despi…
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…
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…
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…
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Shuangpeng Han, Mengmi Zhang
AI models make mistakes when recognizing images-whether in-domain, out-of-domain, or adversarial. Predicting these errors is critical for improving system reliability, reducing cos…
Flow Snapshot Neurons in Action: Deep Neural Networks Generalize to Biological Motion Perception
Shuangpeng Han, Ziyu Wang, Mengmi Zhang
Biological motion perception (BMP) refers to humans' ability to perceive and recognize the actions of living beings solely from their motion patterns, sometimes as minimal as those…
Make Me Happier: Evoking Emotions Through Image Diffusion Models
Qing Lin, Jingfeng Zhang, Yew-Soon Ong +1
Despite the rapid progress in image generation, emotional image editing remains under-explored. The semantics, context, and structure of an image can evoke emotional responses, mak…