5.8k citations · 6.6k across the 7 of their papers we have counts for
11 papers
OlmoEarth v1.3: Embeddings
Gabriel Tseng, Favyen Bastani, Patrick Alan Johnson +13
We make some OlmoEarth embeddings. To do this, we train a new model: OlmoEarth v1.3. OlmoEarth v1.3 is designed to condense multimodal, multitemporal remote sensing data into a sin…
OlmoEarth v1.2: A more efficient family of OlmoEarth models
Gabriel Tseng, Yawen Zhang, Favyen Bastani +8
We present a set of improvements to the OlmoEarth family. These improvements allow us to cut compute costs during training ( reduction in GPU hours required to train ou…
OlmoEarth: Stable Latent Image Modeling for Multimodal Earth Observation
Henry Herzog, Favyen Bastani, Yawen Zhang +23
Earth observation data presents a unique challenge: it is spatial like images, sequential like video or text, and highly multimodal. We present OlmoEarth: a multimodal, spatio-temp…
High-Resolution Live Fuel Moisture Content (LFMC) Maps for Wildfire Risk from Multimodal Earth Observation Data
Patrick Alan Johnson, Gabriel Tseng, Yawen Zhang +5
Wildfires are increasing in intensity and severity at an alarming rate. Recent advances in AI and publicly available satellite data enable monitoring critical wildfire risk factors…
YOLOv3: An Incremental Improvement
Joseph Redmon, Ali Farhadi
We present some updates to YOLO! We made a bunch of little design changes to make it better. We also trained this new network that's pretty swell. It's a little bigger than last ti…
Who Let The Dogs Out? Modeling Dog Behavior From Visual Data
Kiana Ehsani, Hessam Bagherinezhad, Joseph Redmon +2
We introduce the task of directly modeling a visually intelligent agent. Computer vision typically focuses on solving various subtasks related to visual intelligence. We depart fro…
IQA: Visual Question Answering in Interactive Environments
Daniel Gordon, Aniruddha Kembhavi, Mohammad Rastegari +3
We introduce Interactive Question Answering (IQA), the task of answering questions that require an autonomous agent to interact with a dynamic visual environment. IQA presents the…
YOLO9000: Better, Faster, Stronger
Joseph Redmon, Ali Farhadi
We introduce YOLO9000, a state-of-the-art, real-time object detection system that can detect over 9000 object categories. First we propose various improvements to the YOLO detectio…
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
Mohammad Rastegari, Vicente Ordonez, Joseph Redmon +1
We propose two efficient approximations to standard convolutional neural networks: Binary-Weight-Networks and XNOR-Networks. In Binary-Weight-Networks, the filters are approximated…
You Only Look Once: Unified, Real-Time Object Detection
Joseph Redmon, Santosh Divvala, Ross Girshick +1
We present YOLO, a new approach to object detection. Prior work on object detection repurposes classifiers to perform detection. Instead, we frame object detection as a regression…
Real-Time Grasp Detection Using Convolutional Neural Networks
Joseph Redmon, Anelia Angelova
We present an accurate, real-time approach to robotic grasp detection based on convolutional neural networks. Our network performs single-stage regression to graspable bounding box…