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Multi-view stereo: A tutorial
This tutorial presents a hands-on view of the field of multi-view stereo with a focus on
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …
On the synergies between machine learning and binocular stereo for depth estimation from images: A survey
Stereo matching is one of the longest-standing problems in computer vision with close to 40
years of studies and research. Throughout the years the paradigm has shifted from local …
years of studies and research. Throughout the years the paradigm has shifted from local …
Iterative geometry encoding volume for stereo matching
Abstract Recurrent All-Pairs Field Transforms (RAFT) has shown great potentials in
matching tasks. However, all-pairs correlations lack non-local geometry knowledge and …
matching tasks. However, all-pairs correlations lack non-local geometry knowledge and …
Unifying flow, stereo and depth estimation
We present a unified formulation and model for three motion and 3D perception tasks:
optical flow, rectified stereo matching and unrectified stereo depth estimation from posed …
optical flow, rectified stereo matching and unrectified stereo depth estimation from posed …
The surprising effectiveness of diffusion models for optical flow and monocular depth estimation
S Saxena, C Herrmann, J Hur, A Kar… - Advances in …, 2023 - proceedings.neurips.cc
Denoising diffusion probabilistic models have transformed image generation with their
impressive fidelity and diversity. We show that they also excel in estimating optical flow and …
impressive fidelity and diversity. We show that they also excel in estimating optical flow and …
Gmflow: Learning optical flow via global matching
Learning-based optical flow estimation has been dominated with the pipeline of cost volume
with convolutions for flow regression, which is inherently limited to local correlations and …
with convolutions for flow regression, which is inherently limited to local correlations and …
Amt: All-pairs multi-field transforms for efficient frame interpolation
Abstract We present All-Pairs Multi-Field Transforms (AMT), a new network architecture for
video frame interpolation. It is based on two essential designs. First, we build bidirectional …
video frame interpolation. It is based on two essential designs. First, we build bidirectional …
Cat-seg: Cost aggregation for open-vocabulary semantic segmentation
Open-vocabulary semantic segmentation presents the challenge of labeling each pixel
within an image based on a wide range of text descriptions. In this work we introduce a …
within an image based on a wide range of text descriptions. In this work we introduce a …
Cost aggregation with 4d convolutional swin transformer for few-shot segmentation
This paper presents a novel cost aggregation network, called Volumetric Aggregation with
Transformers (VAT), for few-shot segmentation. The use of transformers can benefit …
Transformers (VAT), for few-shot segmentation. The use of transformers can benefit …
Nerfingmvs: Guided optimization of neural radiance fields for indoor multi-view stereo
In this work, we present a new multi-view depth estimation method that utilizes both
conventional SfM reconstruction and learning-based priors over the recently proposed …
conventional SfM reconstruction and learning-based priors over the recently proposed …