12 citations · 23 across the 4 of their papers we have counts for
5 papers
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos
Jennifer J. Sun, Lili Karashchuk, Amil Dravid +9
Quantifying motion in 3D is important for studying the behavior of humans and other animals, but manual pose annotations are expensive and time-consuming to obtain. Self-supervised…
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…
Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions
Serim Ryou, Michael R. Maser, Alexander Y. Cui +3
We present a systematic investigation using graph neural networks (GNNs) to model organic chemical reactions. To do so, we prepared a dataset collection of four ubiquitous reaction…
Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
Serim Ryou, Seong-Gyun Jeong, Pietro Perona
We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample. Deep neural network architectures in image classific…