Zhang, He Riggan, Benjamin S. Hu, Shuowen Short, Nathaniel J. Patel, Vishal M.
Published in
International Journal of Computer Vision
The large domain discrepancy between faces captured in polarimetric (or conventional) thermal and visible domains makes cross-domain face verification a highly challenging problem for human examiners as well as computer vision algorithms. Previous approaches utilize either a two-step procedure (visible feature estimation and visible image reconstru...
Goswami, Gaurav Agarwal, Akshay Ratha, Nalini Singh, Richa Vatsa, Mayank
Published in
International Journal of Computer Vision
Deep neural network (DNN) architecture based models have high expressive power and learning capacity. However, they are essentially a black box method since it is not easy to mathematically formulate the functions that are learned within its many layers of representation. Realizing this, many researchers have started to design methods to exploit th...
Ackland, Stephen Chiclana, Francisco Istance, Howell Coupland, Simon
Published in
International Journal of Computer Vision
Tracking the head in a video stream is a common thread seen within computer vision literature, supplying the research community with a large number of challenging and interesting problems. Head pose estimation from monocular cameras is often considered an extended application after the face tracking task has already been performed. This often invol...
Tran, Linh Kossaifi, Jean Panagakis, Yannis Pantic, Maja
Published in
International Journal of Computer Vision
Deep generative models have significantly advanced image generation, enabling generation of visually pleasing images with realistic texture. Apart from the texture, it is the shape geometry of objects that strongly dictates their appearance. However, currently available generative models do not incorporate geometric information into the image gener...
Wu, Shuzhe Kan, Meina Shan, Shiguang Chen, Xilin
Published in
International Journal of Computer Vision
Expressive representations for characterizing face appearances are essential for accurate face detection. Due to different poses, scales, illumination, occlusion, etc, face appearances generally exhibit substantial variations, and the contents of each local region (facial part) vary from one face to another. Current detectors, however, particularly...
Tokmakov, Pavel Schmid, Cordelia Alahari, Karteek
Published in
International Journal of Computer Vision
We study the problem of segmenting moving objects in unconstrained videos. Given a video, the task is to segment all the objects that exhibit independent motion in at least one frame. We formulate this as a learning problem and design our framework with three cues: (1) independent object motion between a pair of frames, which complements object rec...
Duong, Chi Nhan Quach, Kha Gia Luu, Khoa Le, T. Hoang Ngan Savvides, Marios Bui, Tien D.
Published in
International Journal of Computer Vision
This paper presents a novel subject-dependent deep aging path (SDAP), which inherits the merits of both generative probabilistic modeling and inverse reinforcement learning to model the facial structures and the longitudinal face aging process of a given subject. The proposed SDAP is optimized using tractable log-likelihood objective functions with...
Zhang, Shifeng Wen, Longyin Shi, Hailin Lei, Zhen Lyu, Siwei Li, Stan Z.
Published in
International Journal of Computer Vision
In this work, we describe a single-shot scale-aware convolutional neural network based face detector (SFDet). In comparison with the state-of-the-art anchor-based face detection methods, the main advantages of our method are summarized in four aspects. (1) We propose a scale-aware detection network using a wide scale range of layers associated with...
Zhu, Xiangyu Liu, Hao Lei, Zhen Shi, Hailin Yang, Fan Yi, Dong Qi, Guojun Li, Stan Z.
Published in
International Journal of Computer Vision
In real-world face recognition applications, there is a tremendous amount of data with two images for each person. One is an ID photo for face enrollment, and the other is a probe photo captured on spot. Most existing methods are designed for training data with limited breadth (a relatively small number of classes) and sufficient depth (many sample...
Wang, Mengjiao Shu, Zhixin Cheng, Shiyang Panagakis, Yannis Samaras, Dimitris Zafeiriou, Stefanos
Published in
International Journal of Computer Vision
Several factors contribute to the appearance of an object in a visual scene, including pose, illumination, and deformation, among others. Each factor accounts for a source of variability in the data, while the multiplicative interactions of these factors emulate the entangled variability, giving rise to the rich structure of visual object appearanc...
