Unified Simulation, Perception, and Generation of Human Behavior
Not on the map. Why?
Abstract (arXiv)
Understanding and modeling human behavior is fundamental to almost any computer vision and robotics applications that involve humans. In this thesis, we take a holistic approach to human behavior modeling and tackle its three essential aspects -- simulation, perception, and generation. Throughout the thesis, we show how the three aspects are deeply connected and how utilizing and improving one aspect can greatly benefit the other aspects. We also discuss the lessons learned and our vision for what is next for human behavior modeling.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 189 of its 388 references that are in the map. First posted on arXiv 28 Apr 2022.
Builds on
189 of 388 references.
References · 189
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
- 2017Proximal Policy Optimization Algorithmscited by 15,215
- 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,361
- 2020End-to-End Object Detection with Transformerscited by 7,414
- 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
- 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
- 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
- 2013Auto-Encoding Variational Bayescited by 4,053
- 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,811
38 more
- 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
- 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,367
- 2015Variational Inference with Normalizing Flowscited by 2,170
- 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,612
- 2019AMASS: Archive of Motion Capture as Surface Shapescited by 1,236
- 2017A Closer Look at Spatiotemporal Convolutions for Action Recognitioncited by 1,143
- 2013Spectral Networks and Locally Connected Networks on Graphscited by 1,102
- 2015Effective Approaches to Attention-based Neural Machine Translationcited by 1,026
- 2017PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volumecited by 968
- 2018DeepMind Control Suitecited by 956
- 2017End-to-end Recovery of Human Shape and Posecited by 885
- 2015Gated Graph Sequence Neural Networkscited by 796
- 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 695
- 2018Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networkscited by 690
- 2017Wasserstein GANcited by 639
- 2019Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loopcited by 627
- 2019VIBE: Video Inference for Human Body Pose and Shape Estimationcited by 620
- 2021Action-Conditioned 3D Human Motion Synthesis with Transformer VAEcited by 501
- 2016Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervisioncited by 494
- 2021AI Choreographer: Music Conditioned 3D Dance Generation with AIST++cited by 485
- 2020End-to-End Video Instance Segmentation with Transformerscited by 443
- 2020End-to-End Human Pose and Mesh Reconstruction with Transformerscited by 418
- 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 407
- 20183D human pose estimation in video with temporal convolutions and semi-supervised trainingcited by 403
- 2017A simple yet effective baseline for 3d human pose estimationcited by 401
- 2017Wasserstein Auto-Encoderscited by 373
- 2017On human motion prediction using recurrent neural networkscited by 338
- 2021AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecastingcited by 331
- 2021HuMoR: 3D Human Motion Model for Robust Pose Estimationcited by 324
- 2018Learning 3D Human Dynamics from Videocited by 316
- 2017DESIRE: Distant Future Prediction in Dynamic Scenes with Interacting Agentscited by 310
- 2020HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimationcited by 307
- 2013DeepPose: Human Pose Estimation via Deep Neural Networkscited by 305
- 2018SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraintscited by 298
- 2019Resolving 3D Human Pose Ambiguities with 3D Scene Constraintscited by 295
- 2018Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networkscited by 289
- 2020I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Imagecited by 274
- 2019Convolutional Mesh Regression for Single-Image Human Shape Reconstructioncited by 270
50 most cited of 189 All 189 (JSON)
Built on by
Not cited yet.