A review of multimodal image matching: Methods and applications
Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …
similar structure/content from two or more images that are of significant modalities or …
Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review
This paper presents a comprehensive survey on vision-based robotic grasping. We
conclude three key tasks during vision-based robotic grasping, which are object localization …
conclude three key tasks during vision-based robotic grasping, which are object localization …
Emergent correspondence from image diffusion
Finding correspondences between images is a fundamental problem in computer vision. In
this paper, we show that correspondence emerges in image diffusion models without any …
this paper, we show that correspondence emerges in image diffusion models without any …
Lightglue: Local feature matching at light speed
P Lindenberger, PE Sarlin… - Proceedings of the …, 2023 - openaccess.thecvf.com
We introduce LightGlue, a deep neural network that learns to match local features across
images. We revisit multiple design decisions of SuperGlue, the state of the art in sparse …
images. We revisit multiple design decisions of SuperGlue, the state of the art in sparse …
Foundation models in robotics: Applications, challenges, and the future
We survey applications of pretrained foundation models in robotics. Traditional deep
learning models in robotics are trained on small datasets tailored for specific tasks, which …
learning models in robotics are trained on small datasets tailored for specific tasks, which …
Tracking everything everywhere all at once
We present a new test-time optimization method for estimating dense and long-range motion
from a video sequence. Prior optical flow or particle video tracking algorithms typically …
from a video sequence. Prior optical flow or particle video tracking algorithms typically …
Ego4d: Around the world in 3,000 hours of egocentric video
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …
offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household …
Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras
Z Teed, J Deng - Advances in neural information …, 2021 - proceedings.neurips.cc
We introduce DROID-SLAM, a new deep learning based SLAM system. DROID-SLAM
consists of recurrent iterative updates of camera pose and pixelwise depth through a Dense …
consists of recurrent iterative updates of camera pose and pixelwise depth through a Dense …
Sparf: Neural radiance fields from sparse and noisy poses
P Truong, MJ Rakotosaona… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Neural Radiance Field (NeRF) has recently emerged as a powerful representation
to synthesize photorealistic novel views. While showing impressive performance, it relies on …
to synthesize photorealistic novel views. While showing impressive performance, it relies on …
LoFTR: Detector-free local feature matching with transformers
We present a novel method for local image feature matching. Instead of performing image
feature detection, description, and matching sequentially, we propose to first establish pixel …
feature detection, description, and matching sequentially, we propose to first establish pixel …