1 code implementation • 22 Feb 2024 • Changkun Liu, Shuai Chen, Yukun Zhao, Huajian Huang, Victor Prisacariu, Tristan Braud
In addition, we take advantage of the uncertainty for pose refinement to enhance the performance of APR.
no code implementations • 26 Oct 2023 • Xinghui Li, Jingyi Lu, Kai Han, Victor Prisacariu
In this paper, we address the challenge of matching semantically similar keypoints across image pairs.
no code implementations • 25 Jul 2023 • Gratianus Wesley Putra Data, Henry Howard-Jenkins, David Murray, Victor Prisacariu
We propose Cos R-CNN, a simple exemplar-based R-CNN formulation that is designed for online few-shot object detection.
1 code implementation • 31 Aug 2022 • Mohamed Sayed, John Gibson, Jamie Watson, Victor Prisacariu, Michael Firman, Clément Godard
Traditionally, 3D indoor scene reconstruction from posed images happens in two phases: per-image depth estimation, followed by depth merging and surface reconstruction.
2 code implementations • 20 May 2022 • Michael Hobley, Victor Prisacariu
Specifically, we demonstrate that regression from vision transformer features without point-level supervision or reference images is superior to other reference-less methods and is competitive with methods that use reference images.
Ranked #13 on Object Counting on FSC147
1 code implementation • CVPR 2021 • Jamie Watson, Oisin Mac Aodha, Victor Prisacariu, Gabriel Brostow, Michael Firman
We propose ManyDepth, an adaptive approach to dense depth estimation that can make use of sequence information at test time, when it is available.
Monocular Depth Estimation Unsupervised Monocular Depth Estimation
1 code implementation • 8 Apr 2021 • Shuai Chen, ZiRui Wang, Victor Prisacariu
We present a relocalization pipeline, which combines an absolute pose regression (APR) network with a novel view synthesis based direct matching module, offering superior accuracy while maintaining low inference time.
1 code implementation • CVPR 2020 • Shuda Li, Kai Han, Theo W. Costain, Henry Howard-Jenkins, Victor Prisacariu
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
1 code implementation • ECCV 2020 • Feihu Zhang, Xiaojuan Qi, Ruigang Yang, Victor Prisacariu, Benjamin Wah, Philip Torr
State-of-the-art stereo matching networks have difficulties in generalizing to new unseen environments due to significant domain differences, such as color, illumination, contrast, and texture.
no code implementations • 8 May 2019 • Henry Howard-Jenkins, Shuda Li, Victor Prisacariu
We propose a method for room layout estimation that does not rely on the typical box approximation or Manhattan world assumption.
3 code implementations • CVPR 2019 • Feihu Zhang, Victor Prisacariu, Ruigang Yang, Philip H. S. Torr
In the stereo matching task, matching cost aggregation is crucial in both traditional methods and deep neural network models in order to accurately estimate disparities.
Ranked #4 on Stereo Depth Estimation on Spring
no code implementations • ECCV 2018 • Vassileios Balntas, Shuda Li, Victor Prisacariu
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.
no code implementations • CVPR 2018 • Piotr Bilinski, Victor Prisacariu
We propose a novel end-to-end trainable, deep, encoder-decoder architecture for single-pass semantic segmentation.
Ranked #7 on Semantic Segmentation on CamVid