Divide and Fuse: A Re-ranking Approach for Person Re-identification

As re-ranking is a necessary procedure to boost person re-identification (re-ID) performance on large-scale datasets, the diversity of feature becomes crucial to person reID for its importance both on designing pedestrian descriptions and re-ranking based on feature fusion. However, in many circumstances, only one type of pedestrian feature is available. In this paper, we propose a "Divide and use" re-ranking framework for person re-ID. It exploits the diversity from different parts of a high-dimensional feature vector for fusion-based re-ranking, while no other features are accessible. Specifically, given an image, the extracted feature is divided into sub-features. Then the contextual information of each sub-feature is iteratively encoded into a new feature. Finally, the new features from the same image are fused into one vector for re-ranking. Experimental results on two person re-ID benchmarks demonstrate the effectiveness of the proposed framework. Especially, our method outperforms the state-of-the-art on the Market-1501 dataset.Comment: Accepted by BMVC201

OnionNet: Sharing Features in Cascaded Deep Classifiers

The focus of our work is speeding up evaluation of deep neural networks in retrieval scenarios, where conventional architectures may spend too much time on negative examples. We propose to replace a monolithic network with our novel cascade of feature-sharing deep classifiers, called OnionNet, where subsequent stages may add both new layers as well as new feature channels to the previous ones. Importantly, intermediate feature maps are shared among classifiers, preventing them from the necessity of being recomputed. To accomplish this, the model is trained end-to-end in a principled way under a joint loss. We validate our approach in theory and on a synthetic benchmark. As a result demonstrated in three applications (patch matching, object detection, and image retrieval), our cascade can operate significantly faster than both monolithic networks and traditional cascades without sharing at the cost of marginal decrease in precision.Comment: Accepted to BMVC 201

Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos

In this work, we propose an approach to the spatiotemporal localisation (detection) and classification of multiple concurrent actions within temporally untrimmed videos. Our framework is composed of three stages. In stage 1, appearance and motion detection networks are employed to localise and score actions from colour images and optical flow. In stage 2, the appearance network detections are boosted by combining them with the motion detection scores, in proportion to their respective spatial overlap. In stage 3, sequences of detection boxes most likely to be associated with a single action instance, called action tubes, are constructed by solving two energy maximisation problems via dynamic programming. While in the first pass, action paths spanning the whole video are built by linking detection boxes over time using their class-specific scores and their spatial overlap, in the second pass, temporal trimming is performed by ensuring label consistency for all constituting detection boxes. We demonstrate the performance of our algorithm on the challenging UCF101, J-HMDB-21 and LIRIS-HARL datasets, achieving new state-of-the-art results across the board and significantly increasing detection speed at test time. We achieve a huge leap forward in action detection performance and report a 20% and 11% gain in mAP (mean average precision) on UCF-101 and J-HMDB-21 datasets respectively when compared to the state-of-the-art.Comment: Accepted by British Machine Vision Conference 201

Spatio-Temporal Action Detection with Cascade Proposal and Location Anticipation

In this work, we address the problem of spatio-temporal action detection in temporally untrimmed videos. It is an important and challenging task as finding accurate human actions in both temporal and spatial space is important for analyzing large-scale video data. To tackle this problem, we propose a cascade proposal and location anticipation (CPLA) model for frame-level action detection. There are several salient points of our model: (1) a cascade region proposal network (casRPN) is adopted for action proposal generation and shows better localization accuracy compared with single region proposal network (RPN); (2) action spatio-temporal consistencies are exploited via a location anticipation network (LAN) and thus frame-level action detection is not conducted independently. Frame-level detections are then linked by solving an linking score maximization problem, and temporally trimmed into spatio-temporal action tubes. We demonstrate the effectiveness of our model on the challenging UCF101 and LIRIS-HARL datasets, both achieving state-of-the-art performance.Comment: Accepted at BMVC 2017 (oral

Producing innovation: Comments on Lee and Yu (2010)

The purpose of the article being reviewed (Lee and Yu, 2010), a survey by questionnaire with 182 valid responses, is to analyze “how different relationship styles of employees in the hi-tech industry influence innovation performance” and indeed its conclusions are that “the relationship style of an organization has a significant positive effect on innovation performance”. We see Lee and Yu (2010) as being similar to another highly cited article by Morgan and Hunt in so far as both articles are about relationships, cooperation and trust

The Peter Humphrey/Yu Yingzeng Case and Business Intelligence in China

The case of Peter Humphrey and Yu Yingzeng, convicted in China on August 2014 on charges of unlawful acquisition of citizens’ personal information, raises important issues about Chinese law. A narrow but important issue is how Chinese law draws the line between lawful and unlawful acquisition of information, a practice routinely carried out by businesses and individuals. This article examines the trial transcript and judgment in the Humphrey/Yu case and finds that it sheds regrettably little light on what remains a murky question. A broader issue is whether the Chinese legal system can be counted on to operate in a fair and impartial manner. This article presents the results of a study of all reported cases in Shanghai (ninety-two cases) involving the same provision of the Criminal Law that was the basis of the Humphrey/Yu conviction. It finds that the Humphrey/Yu sentences are outliers relative to other cases with comparable facts. In particular, Humphrey’s sentence of 30 months’ imprisonment was by far the heaviest sentence ever meted out by Shanghai courts, even though the circumstances seem conspicuously less serious than those of many other cases where lesser sentences were imposed

Induction of chromosome damage by ultraviolet light and caffeine: Correlation of cytogenetic evaluation and flow karyotype

Asynchrononously growing cells of a M3-1 Chinese hamster line were ultraviolet (UV) irradiated ( = 254 nm) with UV fluences up to 7.5 J/m2. After irradiation, cells were incubated with or without 2 mM caffeine for 20 hr, then mitotic cells were selected by mechanical shaking. Their chromosomes were isolated, stained with Hoechst 33258 and chromomycin A3, and measured flow cytometrically. While the fluorescence distributions of chromosomes (flow karyotypes) from cells treated with UV alone or with caffeine alone were very similar to those of untreated controls, the flow karyo-types of UV + caffeine-treated cells showed a debris continuum that increased with increasing UV fluence suggesting an increased number of chromosome fragments. Visual evaluation of metaphase plates revealed that the percentage of cells with chromosome damage also increased steadily with increasing UV fluence. A high degree of correlation was observed between the relative magnitude of the debris level from flow karyotypes and the percentage of cells with chromosome damage and with generalized chromosome shattering, respectively, as determined from metaphase spreads

А. Yu. Krymskyi about the history of consonantal system oof the Ukrainian language

Досліджено погляди А. Ю. Кримського на історію розвитку українського консонантизму. Твердження вченого проаналізовано в широкому контексті мовознавства 70-х рр. ХІХ ст. – 30-х рр. ХХ ст. Визначено, які тези вченого зберегли свою актуальність для сучасного мовознавства. The article is devoted to the study of A. Yu. Krymskyi’s views on the development of Ukrainian consonantal system. The scholar’s ideas are analysed at the background of Ukrainian Linguistics of the 70s of the 19th c. – 30s of the 20th c. The author states what A. Yu. Krymskyi’s ideas have preserved their topicality for modern Linguistics