25 Result(s)
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Chapter and Conference Paper
Descriptive Attributes for Language-Based Object Keypoint Detection
Multimodal vision and language (VL) models have recently shown strong performance in phrase grounding and object detection for both zero-shot and finetuned cases. We adapt a VL model (GLIP) for keypoint detect...
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Article
Open AccessOccluded Video Instance Segmentation: A Benchmark
Can our video understanding systems perceive objects when a heavy occlusion exists in a scene? To answer this question, we collect a large-scale dataset called OVIS for occluded video instance segmentation, th...
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Article
Convolutional Networks with Adaptive Inference Graphs
Do convolutional networks really need a fixed feed-forward structure? What if, after identifying the high-level concept of an image, a network could move directly to a layer that can distinguish fine-grained d...
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Chapter and Conference Paper
Deep Fundamental Matrix Estimation Without Correspondences
Estimating fundamental matrices is a classic problem in computer vision. Traditional methods rely heavily on the correctness of estimated key-point correspondences, which can be noisy and unreliable. As a resu...
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Chapter and Conference Paper
Learning Single-View 3D Reconstruction with Limited Pose Supervision
It is expensive to label images with 3D structure or precise camera pose. Yet, this is precisely the kind of annotation required to train single-view 3D reconstruction models. In contrast, unlabeled images or ...
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Chapter and Conference Paper
Multimodal Unsupervised Image-to-Image Translation
Unsupervised image-to-image translation is an important and challenging problem in computer vision. Given an image in the source domain, the goal is to learn the conditional distribution of corresponding image...
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Chapter and Conference Paper
Convolutional Networks with Adaptive Inference Graphs
Do convolutional networks really need a fixed feed-forward structure? What if, after identifying the high-level concept of an image, a network could move directly to a layer that can distinguish fine-grained d...
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Chapter
Cross-View Image Geo-localization
The recent availability of large amounts of geo-tagged imagery has inspired a number of data-driven solutions to the image geo-localization problem. Existing approaches predict the location of a query image by...
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Article
Editorial: Special Issue on Active and Interactive Methods in Computer Vision
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Article
The Ignorant Led by the Blind: A Hybrid Human–Machine Vision System for Fine-Grained Categorization
We present a visual recognition system for fine-grained visual categorization. The system is composed of a human and a machine working together and combines the complementary strengths of computer vision algor...
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Chapter and Conference Paper
Microsoft COCO: Common Objects in Context
We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object recognition in the context of the broader question of scene understanding. This ...
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Chapter and Conference Paper
JBoost Optimization of Color Detectors for Autonomous Underwater Vehicle Navigation
In the world of autonomous underwater vehicles (AUV) the prominent form of sensing is sonar due to cloudy water conditions and dispersion of light. Although underwater conditions are highly suitable for sonar,...
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Article
Open AccessGlobally Optimal Algorithms for Stratified Autocalibration
We present practical algorithms for stratified autocalibration with theoretical guarantees of global optimality. Given a projective reconstruction, we first upgrade it to affine by estimating the position of t...
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Article
Practical Global Optimization for Multiview Geometry
This paper presents a practical method for finding the provably globally optimal solution to numerous problems in projective geometry including multiview triangulation, camera resectioning and homography esti...
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Article
A Feature-based Approach for Dense Segmentation and Estimation of Large Disparity Motion
We present a novel framework for motion segmentation that combines the concepts of layer-based methods and feature-based motion estimation. We estimate the initial correspondences by comparing vectors of filte...
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Chapter and Conference Paper
Structure from Periodic Motion
We show how to exploit temporal periodicity of moving objects to perform 3D reconstruction. The collection of period-separated frames serve as a surrogate for multiple rigid views of a particular pose of the m...
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Chapter and Conference Paper
Practical Global Optimization for Multiview Geometry
This paper presents a practical method for finding the provably globally optimal solution to numerous problems in projective geometry including multiview triangulation, camera resectioning and homography estim...
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Chapter and Conference Paper
On Refractive Optical Flow
This paper presents a novel generalization of the optical flow equation to the case of refraction, and it describes a method for recovering the refractive structure of an object from a video sequence acquired ...
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Chapter and Conference Paper
A Feature-Based Approach for Determining Dense Long Range Correspondences
Planar motion models can provide gross motion estimation and good segmentation for image pairs with large inter-frame disparity. However, as the disparity becomes larger, the resulting dense correspondences wi...
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Chapter and Conference Paper
Spectral Partitioning with Indefinite Kernels Using the Nyström Extension
Fowlkes et al. [7] recently introduced an approximation to the Normalized Cut (NCut) grou** algorithm [18] based on random subsampling and the Nyström extension. As presented, their method is restricted to the ...
