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Found 8 papers, 3 papers with code
SIM2E: Benchmarking the Group Equivariant Capability of Correspondence Matching Algorithms
The experimental results demonstrate the importance of group equivariant algorithms for correspondence matching on various sim(2) transformation conditions.
$\mathbb{X}$Resolution Correspondence Networks
In this paper, we aim at establishing accurate dense correspondences between a pair of images with overlapping field of view under challenging illumination variation, viewpoint changes, and style differences.
Dual-Resolution Correspondence Networks
The fine-resolution feature maps are used to obtain the final dense correspondences guided by the refined coarse 4D correlation tensor.
Correspondence Networks with Adaptive Neighbourhood Consensus
This is a challenging task due to large intra-class variations and a lack of dense pixel level annotations.
Ranked #11 on
Semantic correspondence
on PF-PASCAL
FlowNet3D++: Geometric Losses For Deep Scene Flow Estimation
We present FlowNet3D++, a deep scene flow estimation network.
Thinking Outside the Box: Generation of Unconstrained 3D Room Layouts
We propose a method for room layout estimation that does not rely on the typical box approximation or Manhattan world assumption.
RelocNet: Continuous Metric Learning Relocalisation using Neural Nets
We propose a method of learning suitable convolutional representations for camera pose retrieval based on nearest neighbour matching and continuous metric learning-based feature descriptors.
HDRFusion: HDR SLAM using a low-cost auto-exposure RGB-D sensor
We describe a new method for comparing frame appearance in a frame-to-model 3-D mapping and tracking system using an low dynamic range (LDR) RGB-D camera which is robust to brightness changes caused by auto exposure.
