Navigate
407 papers with code • 0 benchmarks • 1 datasets
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Libraries
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G-VUE
Most implemented papers
DD-PPO: Learning Near-Perfect PointGoal Navigators from 2.5 Billion Frames
facebookresearch/habitat-api
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ICLR 2020
We leverage this scaling to train an agent for 2. 5 Billion steps of experience (the equivalent of 80 years of human experience) -- over 6 months of GPU-time training in under 3 days of wall-clock time with 64 GPUs.
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
shehzaadzd/MINERVA
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ICLR 2018
Knowledge bases (KB), both automatically and manually constructed, are often incomplete --- many valid facts can be inferred from the KB by synthesizing existing information.
Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks
agrimgupta92/sgan
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CVPR 2018
Understanding human motion behavior is critical for autonomous moving platforms (like self-driving cars and social robots) if they are to navigate human-centric environments.
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning
mfe7/cadrl_ros
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This work extends our previous approach to develop an algorithm that learns collision avoidance among a variety of types of dynamic agents without assuming they follow any particular behavior rules.
ViZDoom Competitions: Playing Doom from Pixels
mwydmuch/ViZDoom
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The results of the competition lead to the conclusion that, although reinforcement learning can produce capable Doom bots, they still are not yet able to successfully compete against humans in this game.
Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning
vita-epfl/DyNav
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We propose to (i) rethink pairwise interactions with a self-attention mechanism, and (ii) jointly model Human-Robot as well as Human-Human interactions in the deep reinforcement learning framework.
DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
KupynOrest/DeblurGANv2
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ICCV 2019
We present a new end-to-end generative adversarial network (GAN) for single image motion deblurring, named DeblurGAN-v2, which considerably boosts state-of-the-art deblurring efficiency, quality, and flexibility.
Embodied Question Answering
We present a new AI task -- Embodied Question Answering (EmbodiedQA) -- where an agent is spawned at a random location in a 3D environment and asked a question ("What color is the car?").
Learning to Navigate in Cities Without a Map
deepmind/streetlearn
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NeurIPS 2018
We present an interactive navigation environment that uses Google StreetView for its photographic content and worldwide coverage, and demonstrate that our learning method allows agents to learn to navigate multiple cities and to traverse to target destinations that may be kilometres away.
Meta-Learning through Hebbian Plasticity in Random Networks
enajx/HebbianMetaLearning
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NeurIPS 2020
We find that starting from completely random weights, the discovered Hebbian rules enable an agent to navigate a dynamical 2D-pixel environment; likewise they allow a simulated 3D quadrupedal robot to learn how to walk while adapting to morphological damage not seen during training and in the absence of any explicit reward or error signal in less than 100 timesteps.
