18 citations · 33 across the 5 of their papers we have counts for
8 papers
Substructure-Atom Cross Attention for Molecular Representation Learning
Jiye Kim, Seungbeom Lee, Dongwoo Kim +2
Designing a neural network architecture for molecular representation is crucial for AI-driven drug discovery and molecule design. In this work, we propose a new framework for molec…
Rebooting ACGAN: Auxiliary Classifier GANs with Stable Training
Minguk Kang, Woohyeon Shim, Minsu Cho +1
Conditional Generative Adversarial Networks (cGAN) generate realistic images by incorporating class information into GAN. While one of the most popular cGANs is an auxiliary classi…
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
Hyunsoo Chung, Jungtaek Kim, Boris Knyazev +4
Discovering a solution in a combinatorial space is prevalent in many real-world problems but it is also challenging due to diverse complex constraints and the vast number of possib…
Deep Hough Voting for Robust Global Registration
Junha Lee, Seungwook Kim, Minsu Cho +1
Point cloud registration is the task of estimating the rigid transformation that aligns a pair of point cloud fragments. We present an efficient and robust framework for pairwise r…
Self-Calibrating Neural Radiance Fields
Yoonwoo Jeong, Seokjun Ahn, Christopher Choy +3
In this work, we propose a camera self-calibration algorithm for generic cameras with arbitrary non-linear distortions. We jointly learn the geometry of the scene and the accurate…
Realistic Image Synthesis with Configurable 3D Scene Layouts
Jaebong Jeong, Janghun Jo, Jingdong Wang +2
Recent conditional image synthesis approaches provide high-quality synthesized images. However, it is still challenging to accurately adjust image contents such as the positions an…