154 citations · 258 across the 9 of their papers we have counts for
11 papers
NinjaDesc: Content-Concealing Visual Descriptors via Adversarial Learning
Tony Ng, Hyo Jin Kim, Vincent Lee +7
In the light of recent analyses on privacy-concerning scene revelation from visual descriptors, we develop descriptors that conceal the input image content. In particular, we propo…
Reassessing the Limitations of CNN Methods for Camera Pose Regression
Tony Ng, Adrian Lopez-Rodriguez, Vassileios Balntas +1
In this paper, we address the problem of camera pose estimation in outdoor and indoor scenarios. In comparison to the currently top-performing methods that rely on 2D to 3D matchin…
HyNet: Learning Local Descriptor with Hybrid Similarity Measure and Triplet Loss
Yurun Tian, Axel Barroso-Laguna, Tony Ng +2
Recent works show that local descriptor learning benefits from the use of L2 normalisation, however, an in-depth analysis of this effect lacks in the literature. In this paper, we…
D2D: Keypoint Extraction with Describe to Detect Approach
Yurun Tian, Vassileios Balntas, Tony Ng +3
In this paper, we present a novel approach that exploits the information within the descriptor space to propose keypoint locations. Detect then describe, or detect and describe joi…
UR2KiD: Unifying Retrieval, Keypoint Detection, and Keypoint Description without Local Correspondence Supervision
Tsun-Yi Yang, Duy-Kien Nguyen, Huub Heijnen +1
In this paper, we explore how three related tasks, namely keypoint detection, description, and image retrieval can be jointly tackled using a single unified framework, which is tra…
SOLAR: Second-Order Loss and Attention for Image Retrieval
Tony Ng, Vassileios Balntas, Yurun Tian +1
Recent works in deep-learning have shown that second-order information is beneficial in many computer-vision tasks. Second-order information can be enforced both in the spatial con…
SOSNet: Second Order Similarity Regularization for Local Descriptor Learning
Yurun Tian, Xin Yu, Bin Fan +3
Despite the fact that Second Order Similarity (SOS) has been used with significant success in tasks such as graph matching and clustering, it has not been exploited for learning lo…
Learning Deep Convolutional Embeddings for Face Representation Using Joint Sample- and Set-based Supervision
Baris Gecer, Vassileios Balntas, Tae-Kyun Kim
In this work, we investigate several methods and strategies to learn deep embeddings for face recognition, using joint sample- and set-based optimization. We explain our framework…
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors
Vassileios Balntas, Karel Lenc, Andrea Vedaldi +1
In this paper, we propose a novel benchmark for evaluating local image descriptors. We demonstrate that the existing datasets and evaluation protocols do not specify unambiguously…
Siamese Regression Networks with Efficient mid-level Feature Extraction for 3D Object Pose Estimation
Andreas Doumanoglou, Vassileios Balntas, Rigas Kouskouridas +1
In this paper we tackle the problem of estimating the 3D pose of object instances, using convolutional neural networks. State of the art methods usually solve the challenging probl…
PN-Net: Conjoined Triple Deep Network for Learning Local Image Descriptors
Vassileios Balntas, Edward Johns, Lilian Tang +1
In this paper we propose a new approach for learning local descriptors for matching image patches. It has recently been demonstrated that descriptors based on convolutional neural…