259 citations · 803 across the 48 of their papers we have counts for
9 papers · 1 filter
Proximal Mean-field for Neural Network Quantization
Thalaiyasingam Ajanthan, Puneet K. Dokania, Richard Hartley +1
Compressing large Neural Networks (NN) by quantizing the parameters, while maintaining the performance is highly desirable due to reduced memory and time complexity. In this work,…
Bringing a Blurry Frame Alive at High Frame-Rate with an Event Camera
Liyuan Pan, Cedric Scheerlinck, Xin Yu +3
Event-based cameras can measure intensity changes (called `{\it events}') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the active pix…
Generalized Range Moves
Richard Hartley, Thalaiyasingam Ajanthan
We consider move-making algorithms for energy minimization of multi-label Markov Random Fields (MRFs). Since this is not a tractable problem in general, a commonly used heuristic i…
Scalable Deep -Subspace Clustering
Tong Zhang, Pan Ji, Mehrtash Harandi +2
Subspace clustering algorithms are notorious for their scalability issues because building and processing large affinity matrices are demanding. In this paper, we introduce a metho…
Phase-only Image Based Kernel Estimation for Single-image Blind Deblurring
Liyuan Pan, Richard Hartley, Miaomiao Liu +1
The image blurring process is generally modelled as the convolution of a blur kernel with a latent image. Therefore, the estimation of the blur kernel is essentially important for…
Block Mean Approximation for Efficient Second Order Optimization
Yao Lu, Mehrtash Harandi, Richard Hartley +1
Advanced optimization algorithms such as Newton method and AdaGrad benefit from second order derivative or second order statistics to achieve better descent directions and faster c…
Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective
Jing Zhang, Tong Zhang, Yuchao Dai +2
The success of current deep saliency detection methods heavily depends on the availability of large-scale supervision in the form of per-pixel labeling. Such supervision, while lab…
Non-Linear Temporal Subspace Representations for Activity Recognition
Anoop Cherian, Suvrit Sra, Stephen Gould +1
Representations that can compactly and effectively capture the temporal evolution of semantic content are important to computer vision and machine learning algorithms that operate…
Identity-preserving Face Recovery from Portraits
Fatemeh Shiri, Xin Yu, Fatih Porikli +2
Recovering the latent photorealistic faces from their artistic portraits aids human perception and facial analysis. However, a recovery process that can preserve identity is challe…