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Found 8 papers, 3 papers with code
GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
The Embodied AI community has made significant strides in visual navigation tasks, exploring targets from 3D coordinates, objects, language descriptions, and images.
Seeing the Unseen: Visual Common Sense for Semantic Placement
Datasets for image description are typically constructed by curating relevant images and asking humans to annotate the contents of the image; neither of those two steps are straightforward for objects not present in the image.
OVRL-V2: A simple state-of-art baseline for ImageNav and ObjectNav
We present a single neural network architecture composed of task-agnostic components (ViTs, convolutions, and LSTMs) that achieves state-of-art results on both the ImageNav ("go to location in <this picture>") and ObjectNav ("find a chair") tasks without any task-specific modules like object detection, segmentation, mapping, or planning modules.
PIRLNav: Pretraining with Imitation and RL Finetuning for ObjectNav
We find that BC$\rightarrow$RL on human demonstrations outperforms BC$\rightarrow$RL on SP and FE trajectories, even when controlled for same BC-pretraining success on train, and even on a subset of val episodes where BC-pretraining success favors the SP or FE policies.
Habitat-Matterport 3D Semantics Dataset
The scale, quality, and diversity of object annotations far exceed those of prior datasets.
Offline Visual Representation Learning for Embodied Navigation
In this paper, we show that an alternative 2-stage strategy is far more effective: (1) offline pretraining of visual representations with self-supervised learning (SSL) using large-scale pre-rendered images of indoor environments (Omnidata), and (2) online finetuning of visuomotor representations on specific tasks with image augmentations under long learning schedules.
Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale
We present a large-scale study of imitating human demonstrations on tasks that require a virtual robot to search for objects in new environments -- (1) ObjectGoal Navigation (e. g. 'find & go to a chair') and (2) Pick&Place (e. g. 'find mug, pick mug, find counter, place mug on counter').
Fabrik: An Online Collaborative Neural Network Editor
We present Fabrik, an online neural network editor that provides tools to visualize, edit, and share neural networks from within a browser.
