29 citations · 38 across the 2 of their papers we have counts for
5 papers
Improving Generative Imagination in Object-Centric World Models
Zhixuan Lin, Yi-Fu Wu, Skand Peri +3
The remarkable recent advances in object-centric generative world models raise a few questions. First, while many of the recent achievements are indispensable for making a general…
Generative Neurosymbolic Machines
Jindong Jiang, Sungjin Ahn
Reconciling symbolic and distributed representations is a crucial challenge that can potentially resolve the limitations of current deep learning. Remarkable advances in this direc…
SPACE: Unsupervised Object-Oriented Scene Representation via Spatial Attention and Decomposition
Zhixuan Lin, Yi-Fu Wu, Skand Vishwanath Peri +5
The ability to decompose complex multi-object scenes into meaningful abstractions like objects is fundamental to achieve higher-level cognition. Previous approaches for unsupervise…
SCALOR: Generative World Models with Scalable Object Representations
Jindong Jiang, Sepehr Janghorbani, Gerard de Melo +1
Scalability in terms of object density in a scene is a primary challenge in unsupervised sequential object-oriented representation learning. Most of the previous models have been s…
RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation
Jindong Jiang, Lunan Zheng, Fei Luo +1
Indoor semantic segmentation has always been a difficult task in computer vision. In this paper, we propose an RGB-D residual encoder-decoder architecture, named RedNet, for indoor…