The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website 1 .

Offline training for object tracking has recently shown great potentials in balancing tracking accuracy and speed. However, it is still difficult to adapt an offline trained model to a target tracked online. This work presents a Residual Attentional Siamese Network (RASNet) for high performance object tracking. The RASNet model reformulates the correlation filter within a Siamese tracking framework, and introduces different kinds of the attention mechanisms to adapt the model without updating the model online. In particular, by exploiting the offline trained general attention, the target adapted residual attention, and the channel favored feature attention, the RASNet not only mitigates the over-fitting problem in deep network training, but also enhances its discriminative capacity and adaptability due to the separation of representation learning and discriminator learning. The proposed deep architecture is trained from end to end and takes full advantage of the rich spatial temporal information to achieve robust visual tracking. Experimental results on two latest benchmarks, OTB-2015 and VOT2017, show that the RASNet tracker has the state-of-the-art tracking accuracy while runs at more than 80 frames per second.

No abstract

The aim of the present study is to investigate the efficacy and safety of dose-dense (biweekly) carboplatin and paclitaxel as a neoadjuvant treatment for operable breast cancer. Patients with previously untreated breast cancer (stages Ic-III) were treated with four cycles of paclitaxel (175 mg/m(2), intravenous drip, D1) and carboplatin (area under the curve of 5, D1). Patients with HER2+ disease simultaneously received trastuzumab (6 mg/kg initial dose with subsequent doses of 4 mg/kg biweekly). The primary endpoint was a pathologically complete response (pCR). Between January 2012 and February 2014, 110 patients were enrolled. The overall pCR rate was 35.45 % (39 of 110). The pCR rates for the different cancer subtypes were as follows: 10.53 % (2 of 19) among the patients with the luminal A subtype, 12.50 % (5 of 40) among the patients with the luminal B (HER2-) subtype, 58.33 % (14 of 24) among the patients with the luminal B (HER2+) subtype, 57.14 % (8 of 14) among the patients with the triple-negative subtype, and 76.92 % (10 of 13) among the patients with the HER2+ subtype. The patients experienced the following toxicity side effects: grade 3/4 neutropenia (N = 27, 24.55 %), grade 3/4 anemia (N = 6, 5.45 %), grade 3/4 thrombocytopenia (N = 2, 1.82 %), grade 3 alanine aminotransferase (ALT) elevation (N = 1, 0.91 %), grade 3 neuropathy (N = 3, 2.73 %), grade 3 pain (N = 2, 1.82 %), and grade 3 fatigue (N = 1, 0.91 %). In total, 19.09 % of the patients experienced treatment delay or discontinuation due to hematological toxicity, and one patient discontinued treatment due to non-hematological toxicity. Neoadjuvant biweekly paclitaxel plus carboplatin is a feasible therapy that achieved high pCR rates in patients with the HER2+, triple-negative, and luminal B (HER2+) cancer subtypes (NCT0205986).