Kautz, Jan

MoCoGAN: Decomposing Motion and Content for Video Generation

Tulyakov, S., Liu, M.-Y., Yang, X., & Kautz, J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Generative Adversarial Networks and Image SynthesisAdvanced Image Processing Techniques

Cited by 1,076

Importance Estimation for Neural Network Pruning

Molchanov, P., Mallya, A., Tyree, S., Frosio, I., & Kautz, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 983

Video-to-Video Synthesis

Wang, T.-C., Liu, M.-Y., Zhu, J.-Y., Liu, G., Tao, A., Kautz, J., & Catanzaro, B. (2018) · arXiv

Generative Adversarial Networks and Image SynthesisAdvanced Image Processing Techniques

Cited by 594

Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion

Yin, H., Molchanov, P., Alvarez, J. M., Li, Z., Mallya, A., Hoiem, D., Jha, N. K., & Kautz, J. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 540

A-ViT: Adaptive Tokens for Efficient Vision Transformer

Yin, H., Vahdat, A., Alvarez, J. M., Mallya, A., Kautz, J., & Molchanov, P. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 360

FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects

Wen, B., Yang, W., Kautz, J., & Birchfield, S. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisRobot Manipulation and Learning

Cited by 353

Pixel-Adaptive Convolutional Neural Networks

Su, H., Jampani, V., Sun, D., Gallo, O., Learned-Miller, E., & Kautz, J. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Image Processing TechniquesAdvanced Neural Network Applications

Cited by 348

FlexISP: a flexible camera image processing framework

Heide, F., Steinberger, M., Tsai, Y.-T., Rouf, M., Pająk, D., Reddy, D., Gallo, O., Liu, J., Heidrich, W., Egiazarian, K., et al. (2014) · ACM Transactions on Graphics

Advanced Image Processing TechniquesImage Enhancement Techniques

Cited by 298

Score-based Generative Modeling in Latent Space

Vahdat, A., Kreis, K., & Kautz, J. (2021) · arXiv

Generative Adversarial Networks and Image SynthesisAdversarial Robustness in Machine Learning

Cited by 224

SpatialRGPT: Grounded Spatial Reasoning in Vision-Language Models

Cheng, A.-C., Yin, H., Fu, Y., Guo, Q., Yang, R., Kautz, J., Wang, X., & Liu, S. (2024) · Advances in Neural Information Processing Systems 37

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 121

SpatialRGPT: Grounded Spatial Reasoning in Vision Language Models

Cheng, A.-C., Yin, H., Fu, Y., Guo, Q., Yang, R., Kautz, J., Wang, X., & Liu, S. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 121

NaVILA: Legged Robot Vision-Language-Action Model for Navigation

Cheng, A.-C., Ji, Y., Yang, Z., Gongye, Z., Zou, X., Kautz, J., Biyik, E., Yin, H., Liu, S., & Wang, X. (2025) · Robotics: Science and Systems XXI

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 54

Parameter Efficient Multimodal Transformers for Video Representation Learning

Lee, S., Yu, Y., Kim, G., Breuel, T., Kautz, J., & Song, Y. (2020) · arXiv

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 49

Sim-to-Real Transfer of Accurate Grasping with Eye-In-Hand Observations and Continuous Control

Yan, M., Frosio, I., Tyree, S., & Kautz, J. (2017) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 31

An Empirical Study of Mamba-based Language Models

Waleffe, R., Byeon, W., Riach, D., Norick, B., Korthikanti, V., Dao, T., Gu, A., Hatamizadeh, A., Singh, S., Narayanan, D., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

One-Minute Video Generation with Test-Time Training

Dalal, K., Koceja, D., Xu, J., Zhao, Y., Han, S., Cheung, K. C., Kautz, J., Choi, Y., Sun, Y., & Wang, X. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 17

GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

NVIDIA, :, Bjorck, J., Castañeda, F., Cherniadev, N., Da, X., Ding, R., Fan, L. "., Fang, Y., Fox, D., et al. (2025) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 10

STORM: Token-Efficient Long Video Understanding for Multimodal LLMs

Jiang, J., Li, X., Liu, Z., Li, M., Chen, G., Li, Z., Huang, D.-A., Liu, G., Yu, Z., Keutzer, K., et al. (2025) · 2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 2

Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models

Li, Z., Chen, G., Liu, S., Wang, S., VS, V., Ji, Y., Lan, S., Zhang, H., Zhao, Y., Radhakrishnan, S., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 2

LongVILA: Scaling Long-Context Visual Language Models for Long Videos

Chen, Y., Xue, F., Li, D., Hu, Q., Zhu, L., Li, X., Fang, Y., Tang, H., Yang, S., Liu, Z., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 2

Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought

Man, Y., Huang, D.-A., Liu, G., Sheng, S., Liu, S., Gui, L.-Y., Kautz, J., Wang, Y.-X., & Yu, Z. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsVisual Attention and Saliency Detection

Cited by 2

Gated Delta Networks: Improving Mamba2 with Delta Rule

Yang, S., Kautz, J., & Hatamizadeh, A. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1

Learning to Discover at Test Time

Yuksekgonul, M., Koceja, D., Li, X., Bianchi, F., McCaleb, J., Wang, X., Kautz, J., Choi, Y., Zou, J., Guestrin, C., et al. (2026) · arXiv

Artificial Intelligence ApplicationsEvolutionary Algorithms and Applications

Cited by 1

World Simulation with Video Foundation Models for Physical AI

NVIDIA, :, Ali, A., Bai, J., Bala, M., Balaji, Y., Blakeman, A., Cai, T., Cao, J., Cao, T., et al. (2025) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 1