Search Results for author: Siyuan Qi

Found 15 papers, 7 papers with code

Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense

no code implementations20 Apr 2020 Yixin Zhu, Tao Gao, Lifeng Fan, Siyuan Huang, Mark Edmonds, Hangxin Liu, Feng Gao, Chi Zhang, Siyuan Qi, Ying Nian Wu, Joshua B. Tenenbaum, Song-Chun Zhu

We demonstrate the power of this perspective to develop cognitive AI systems with humanlike common sense by showing how to observe and apply FPICU with little training data to solve a wide range of challenging tasks, including tool use, planning, utility inference, and social learning.

Common Sense Reasoning Small Data Image Classification

Cascaded Human-Object Interaction Recognition

1 code implementation CVPR 2020 Tianfei Zhou, Wenguan Wang, Siyuan Qi, Haibin Ling, Jianbing Shen

The interaction recognition network has two crucial parts: a relation ranking module for high-quality HOI proposal selection and a triple-stream classifier for relation prediction.

Human-Object Interaction Detection

Learning Compositional Neural Information Fusion for Human Parsing

1 code implementation ICCV 2019 Wenguan Wang, Zhijie Zhang, Siyuan Qi, Jianbing Shen, Yanwei Pang, Ling Shao

The bottom-up and top-down inferences explicitly model the compositional and decompositional relations in human bodies, respectively.

Human Parsing

PerspectiveNet: 3D Object Detection from a Single RGB Image via Perspective Points

no code implementations NeurIPS 2019 Siyuan Huang, Yixin Chen, Tao Yuan, Siyuan Qi, Yixin Zhu, Song-Chun Zhu

Detecting 3D objects from a single RGB image is intrinsically ambiguous, thus requiring appropriate prior knowledge and intermediate representations as constraints to reduce the uncertainties and improve the consistencies between the 2D image plane and the 3D world coordinate.

Monocular 3D Object Detection

Theory-based Causal Transfer: Integrating Instance-level Induction and Abstract-level Structure Learning

no code implementations25 Nov 2019 Mark Edmonds, Xiaojian Ma, Siyuan Qi, Yixin Zhu, Hongjing Lu, Song-Chun Zhu

Given these general theories, the goal is to train an agent by interactively exploring the problem space to (i) discover, form, and transfer useful abstract and structural knowledge, and (ii) induce useful knowledge from the instance-level attributes observed in the environment.

Transfer Learning

Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense

no code implementations ICCV 2019 Yixin Chen, Siyuan Huang, Tao Yuan, Siyuan Qi, Yixin Zhu, Song-Chun Zhu

We propose a new 3D holistic++ scene understanding problem, which jointly tackles two tasks from a single-view image: (i) holistic scene parsing and reconstruction---3D estimations of object bounding boxes, camera pose, and room layout, and (ii) 3D human pose estimation.

3D Human Pose Estimation Human-Object Interaction Detection +1

Human-centric Indoor Scene Synthesis Using Stochastic Grammar

1 code implementation CVPR 2018 Siyuan Qi, Yixin Zhu, Siyuan Huang, Chenfanfu Jiang, Song-Chun Zhu

We present a human-centric method to sample and synthesize 3D room layouts and 2D images thereof, to obtain large-scale 2D/3D image data with perfect per-pixel ground truth.

Indoor Scene Synthesis

Learning Human-Object Interactions by Graph Parsing Neural Networks

1 code implementation ECCV 2018 Siyuan Qi, Wenguan Wang, Baoxiong Jia, Jianbing Shen, Song-Chun Zhu

For a given scene, GPNN infers a parse graph that includes i) the HOI graph structure represented by an adjacency matrix, and ii) the node labels.

Human-Object Interaction Detection

Holistic 3D Scene Parsing and Reconstruction from a Single RGB Image

1 code implementation ECCV 2018 Siyuan Huang, Siyuan Qi, Yixin Zhu, Yinxue Xiao, Yuanlu Xu, Song-Chun Zhu

We propose a computational framework to jointly parse a single RGB image and reconstruct a holistic 3D configuration composed by a set of CAD models using a stochastic grammar model.

Monocular 3D Object Detection Object Localization +3

Generalized Earley Parser: Bridging Symbolic Grammars and Sequence Data for Future Prediction

no code implementations ICML 2018 Siyuan Qi, Baoxiong Jia, Song-Chun Zhu

Future predictions on sequence data (e. g., videos or audios) require the algorithms to capture non-Markovian and compositional properties of high-level semantics.

Activity Prediction Future prediction

Intent-aware Multi-agent Reinforcement Learning

no code implementations6 Mar 2018 Siyuan Qi, Song-Chun Zhu

We experiment our algorithm in a real-world problem that is non-episodic, and the number of agents and goals can vary over time.

Multi-agent Reinforcement Learning reinforcement-learning

Predicting Human Activities Using Stochastic Grammar

no code implementations ICCV 2017 Siyuan Qi, Siyuan Huang, Ping Wei, Song-Chun Zhu

This paper presents a novel method to predict future human activities from partially observed RGB-D videos.

Activity Prediction

Configurable 3D Scene Synthesis and 2D Image Rendering with Per-Pixel Ground Truth using Stochastic Grammars

no code implementations1 Apr 2017 Chenfanfu Jiang, Siyuan Qi, Yixin Zhu, Siyuan Huang, Jenny Lin, Lap-Fai Yu, Demetri Terzopoulos, Song-Chun Zhu

We propose a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with associated ground truth information, for the purposes of training, benchmarking, and diagnosing learning-based computer vision and robotics algorithms.

Scene Understanding Semantic Segmentation

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