Adobe researchers have co-authored twelve main conference papers, including four accepted as oral presentations, and six workshop papers for this year’s Neural Information Processing Systems conference (NeurIPS), held from November 28 to December 9, 2022.
NeurIPS is a multi-track interdisciplinary annual meeting that includes invited talks, demonstrations, symposia, and oral and poster presentations of refereed papers. Alongside the conference is a professional exposition focusing on machine learning in practice, a series of tutorials, and topical workshops that provide a less formal setting for the exchange of ideas.
Nearly all of Adobe’s papers are the result of student internships or other collaborations with university students and faculty. Please check out the Adobe Research careers page to learn more about internships and full-time career opportunities.
Main conference: Adobe co-authored papers
Oral papers
Breaking Bad: A Dataset for Geometric Fracture and Reassembly
Silvia Sellán, Yun-Chun Chen, Ziyi Wu, Animesh Garg, Alec Jacobson
CyCLIP: Cyclic Contrastive Language-Image Pretraining
Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan Rossi, Vishwa Vinay, Aditya Grover
NeuForm: Adaptive Overfitting for Neural Shape Editing
Connor Lin, Niloy Mitra, Gordon Wetzstein, Leonidas Guibas, Paul Guerrero
NeMF: Neural Motion Fields for Kinematic Animation
Chengan He, Jun Saito, James Zachary, Holly Rushmeier, Yi Zhou
Poster papers
Delving into OOD Detection with Vision-Language Representations
Yifei Ming, Ziyang Cai, Jiuxiang Gu, Yiyou Sun, Wei Li, Yixuan Li
Dynamic Tensor Product Regression
Aravind Reddy, Zhao Song, Lichen Zhang
Fast Distance Oracles for Any Symmetric Norm
Yichuan Deng, Zhao Song, Omri Weinstein, Ruizhe Zhang
Monocular Dynamic View Synthesis: A Reality Check
Hang Gao, Ruilong Li, Shubham Tulsiani, Bryan Russell, Angjoo Kanazawa
Root Cause Analysis of Failures in Microservices through Causal Discovery
Azam Ikram, Sarthak Chakraborty, Subrata Mitra, Shiv Saini, Saurabh Bagchi, Murat Kocaoglu
Sample Constrained Treatment Effect Estimation
Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
VectorAdam for Rotation Equivariant Geometry Optimization
Selena Zihan Ling, Nicholas Sharp, Alec Jacobson
VITA: Video Instance Segmentation via Object Token Association
Miran Heo, Sukjun Hwang, Seoung Wug Oh, Joon-Young Lee, Seon Joo Kim
Workshop: Adobe co-authored papers
Contrastive Learning on Synthetic Videos for GAN Latent Disentangling
Kevin Duarte, Wei-An Lin, Ratheesh Kalarot, Jingwan Lu, Eli Shechtman, Shabnam Ghadar, Mubarak Shah
Presented at the workshop Synthetic Data for Empowering ML Research
Improving cross-modal attention via object detection
Yongil Kim, Yerin Hwang, Seunghyun Yoon, Hyeongu Yun, Kyomin Jung
Presented at the workshop All Things Attention: Bridging Different Perspectives on Attention
Trajectory-based Explainability Framework for Offline RL
Shripad Deshmukh, Arpan Dasgupta, Chirag Agarwal, Nan Jiang, Balaji Krishnamurthy, Georgios Theocharous, Jayakumar Subramanian
Presented at the workshop Offline Reinforcement Learning Workshop: Offline RL as a “Launchpad”
Using Informative Data Subsets for Efficient Training of Large Language Models: An Initial Study
H S V N S Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia, Milan Aggarwal, Ganesh Ramakrishnan, Rishabh Iyer
Presented at the workshop Efficient Natural Language and Speech Processing
Videogenic: Video Highlights via Photogenic Moments
David Chuan-En Lin, Fabian Caba, Joon-Young Lee, Oliver Wang, Nikolas Martelaro
Presented at the workshop Machine Learning for Creativity and Design
VideoMap: Video Editing in Latent Space
David Chuan-En Lin, Fabian Caba Heilbron, Joon-Young Lee, Oliver Wang, Nikolas Martelaro
Presented at the workshop Machine Learning for Creativity and Design
Area Chairs
Georgios Theocharous
