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Found 6 papers, 2 papers with code
LineNet: a Zoomable CNN for Crowdsourced High Definition Maps Modeling in Urban Environments
Combining LineNet and TTLane, we proposed a pipeline to model HD maps with crowdsourced data for the first time.
What and Where: A Context-based Recommendation System for Object Insertion
In this work, we propose a novel topic consisting of two dual tasks: 1) given a scene, recommend objects to insert, 2) given an object category, retrieve suitable background scenes.
Recursive-NeRF: An Efficient and Dynamically Growing NeRF
Only query coordinates with high uncertainties are forwarded to the next level to a bigger neural network with a more powerful representational capability.
Can Attention Enable MLPs To Catch Up With CNNs?
In the first week of May, 2021, researchers from four different institutions: Google, Tsinghua University, Oxford University and Facebook, shared their latest work [16, 7, 12, 17] on arXiv. org almost at the same time, each proposing new learning architectures, consisting mainly of linear layers, claiming them to be comparable, or even superior to convolutional-based models.
Are we ready for a new paradigm shift? A Survey on Visual Deep MLP
In the GPU era, the locally and globally weighted summations are the current mainstreams, represented by the convolution and self-attention mechanism, as well as MLP.
