414 citations · 1.1k across the 47 of their papers we have counts for
6 papers · 1 filter
Self-Supervised Keypoint Discovery in Behavioral Videos
Jennifer J. Sun, Serim Ryou, Roni Goldshmid +6
We propose a method for learning the posture and structure of agents from unlabelled behavioral videos. Starting from the observation that behaving agents are generally the main so…
Weakly Supervised Keypoint Discovery
Serim Ryou, Pietro Perona
In this paper, we propose a method for keypoint discovery from a 2D image using image-level supervision. Recent works on unsupervised keypoint discovery reliably discover keypoints…
Multi-Label Learning from Single Positive Labels
Elijah Cole, Oisin Mac Aodha, Titouan Lorieul +3
Predicting all applicable labels for a given image is known as multi-label classification. Compared to the standard multi-class case (where each image has only one label), it is co…
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions
Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty +8
Multi-agent behavior modeling aims to understand the interactions that occur between agents. We present a multi-agent dataset from behavioral neuroscience, the Caltech Mouse Social…
Matched sample selection with GANs for mitigating attribute confounding
Chandan Singh, Guha Balakrishnan, Pietro Perona
Measuring biases of vision systems with respect to protected attributes like gender and age is critical as these systems gain widespread use in society. However, significant correl…
A linearized framework and a new benchmark for model selection for fine-tuning
Aditya Deshpande, Alessandro Achille, Avinash Ravichandran +6
Fine-tuning from a collection of models pre-trained on different domains (a "model zoo") is emerging as a technique to improve test accuracy in the low-data regime. However, model…