63 citations · 437 across the 52 of their papers we have counts for
10 papers · 1 filter
PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning
Yining Hong, Li Yi, Joshua B. Tenenbaum +2
A critical aspect of human visual perception is the ability to parse visual scenes into individual objects and further into object parts, forming part-whole hierarchies. Such compo…
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language
Mingyu Ding, Zhenfang Chen, Tao Du +3
In this work, we propose a unified framework, called Visual Reasoning with Differ-entiable Physics (VRDP), that can jointly learn visual concepts and infer physics models of object…
OPEn: An Open-ended Physics Environment for Learning Without a Task
Chuang Gan, Abhishek Bhandwaldar, Antonio Torralba +2
Humans have mental models that allow them to plan, experiment, and reason in the physical world. How should an intelligent agent go about learning such models? In this paper, we wi…
Adversarial Option-Aware Hierarchical Imitation Learning
Mingxuan Jing, Wenbing Huang, Fuchun Sun +4
It has been a challenge to learning skills for an agent from long-horizon unannotated demonstrations. Existing approaches like Hierarchical Imitation Learning(HIL) are prone to com…
Temporal and Object Quantification Networks
Jiayuan Mao, Zhezheng Luo, Chuang Gan +4
We present Temporal and Object Quantification Networks (TOQ-Nets), a new class of neuro-symbolic networks with a structural bias that enables them to learn to recognize complex rel…
Found a Reason for me? Weakly-supervised Grounded Visual Question Answering using Capsules
Aisha Urooj Khan, Hilde Kuehne, Kevin Duarte +3
The problem of grounding VQA tasks has seen an increased attention in the research community recently, with most attempts usually focusing on solving this task by using pretrained…
PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics
Zhiao Huang, Yuanming Hu, Tao Du +4
Simulated virtual environments serve as one of the main driving forces behind developing and evaluating skill learning algorithms. However, existing environments typically only sim…
Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning
Zhenfang Chen, Jiayuan Mao, Jiajun Wu +3
We study the problem of dynamic visual reasoning on raw videos. This is a challenging problem; currently, state-of-the-art models often require dense supervision on physical object…
The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI
Chuang Gan, Siyuan Zhou, Jeremy Schwartz +8
We introduce a visually-guided and physics-driven task-and-motion planning benchmark, which we call the ThreeDWorld Transport Challenge. In this challenge, an embodied agent equipp…
Learning Task Decomposition with Ordered Memory Policy Network
Yuchen Lu, Yikang Shen, Siyuan Zhou +3
Many complex real-world tasks are composed of several levels of sub-tasks. Humans leverage these hierarchical structures to accelerate the learning process and achieve better gener…