Decode-MOT: How Can We Hurdle Frames to Go Beyond Tracking-by-Detection?

The speed of tracking-by-detection (TBD) greatly depends on the number of running a detector because the detection is the most expensive operation in TBD. In many practical cases, multi-object tracking (MOT) can be, however, achieved based tracking-by-motion (TBM) only. This is a possible solution without much loss of MOT accuracy when the variations of object cardinality and motions are not much within consecutive frames.

Deformable Part Region Learning and Feature Aggregation Tree Representation for Object Detection.

Region-based object detection infers object regions for one or more categories in an image. Due to the recent advances in deep learning and region proposal methods, object detectors based on convolutional neural networks (CNNs) have been flourishing and provided promising detection results. However, the accuracy of the convolutional object detectors can be degraded often due to the low feature discriminability caused by geometric variation or transformation of an object.

Effective Multi-Object Tracking via Global Object Models and Object Constraint Learning.

Effective multi-object tracking is still challenging due to the trade-off between tracking accuracy and speed. Because the recent multi-object tracking (MOT) methods leverage object appearance and motion models so as to associate detections between consecutive frames, the key for effective multi-object tracking is to reduce the computational complexity of learning both models. To this end, this work proposes global appearance and motion models to discriminate multiple objects instead of learning local object-specific models.

Configurationally Random Polythiophene for Improved Polymer Ordering and Charge-Transporting Ability.

Random polythiophene polymers are characterized by the arbitrary sequences of monomeric units along polymer backbones. These untailored orientations generally result in the twisting of thiophene rings out of the conjugation planarity in addition to steric repulsions experienced among substituted alkyl chains. These tendencies have limited close polymer packing, which has been detrimental to charge transport in these moieties.

Electrical Transport and Thermoelectric Properties of SnSe-SnTe Solid Solution.

SnSe is considered as a promising thermoelectric (TE) material since the discovery of the record figure of merit (ZT) of 2.6 at 926 K in single crystal SnSe. It is, however, difficult to use single crystal SnSe for practical applications due to the poor mechanical properties and the difficulty and cost of fabricating a single crystal.

3D Printer-Based Encapsulated Origami Electronics for Extreme System Stretchability and High Areal Coverage.

Stretchability and areal coverage of active devices are critical design considerations of stretchable or wearable photovoltaics and photodetections where high areal coverages are required. However, simultaneously maximizing both properties in conventional island-bridge structures through traditional two-dimensional manufacturing processes is difficult due to their inherent trade-offs. Here, a 3D printer-based strategy to achieve extreme system stretchability and high areal coverage through combining fused deposition modeling (FDM) and flexible conductive nanocomposites is reported.

Controlling the Morphology of Organic-Inorganic Hybrid Perovskites through Dual Additive-Mediated Crystallization for Solar Cell Applications.

To realize a high-efficiency perovskite solar cell (PSC), it is critical to optimize the morphology of the perovskite film for a uniform and smooth finish with large grain size during film formation. Using a chemical compound as an additive to the precursor solution has recently been established as a promising method to control the morphology of the perovskite film. In this study, we propose a new method to achieve an improved morphology of the methylammonium lead iodide perovskite film by simultaneous addition of dimethyl sulfoxide (DMSO) and methoxyammonium salt (MeO) (dual additives).

Solution-Processed Ultrathin TiO Compact Layer Hybridized with Mesoporous TiO for High-Performance Perovskite Solar Cells.

The electron transport layer (ETL) is a key component of perovskite solar cells (PSCs) and must provide efficient electron extraction and collection while minimizing the charge recombination at interfaces in order to ensure high performance. Conventional bilayered TiO ETLs fabricated by depositing compact TiO (c-TiO) and mesoporous TiO (mp-TiO) in sequence exhibit resistive losses due to the contact resistance at the c-TiO/mp-TiO interface and the series resistance arising from the intrinsically low conductivity of TiO. Herein, to minimize such resistive losses, we developed a novel ETL consisting of an ultrathin c-TiO layer hybridized with mp-TiO, which is fabricated by performing one-step spin-coating of a mp-TiO solution containing a small amount of titanium diisopropoxide bis(acetylacetonate) (TAA).

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively.

Performance enhancement of planar heterojunction perovskite solar cells by n-doping of the electron transporting layer.

Herein we report a simple n-doping method to enhance the performance of perovskite solar cells with a planar heterojunction structure. Devices with an n-doped PCBM electron transporting layer exhibit a power conversion efficiency of 13.8% with a remarkably enhanced short-circuit current of 22.

Polyp Detection via Imbalanced Learning and Discriminative Feature Learning.

Recent achievement of the learning-based classification leads to the noticeable performance improvement in automatic polyp detection. Here, building large good datasets is very crucial for learning a reliable detector. However, it is practically challenging due to the diversity of polyp types, expensive inspection, and labor-intensive labeling tasks.

Robust online multiobject tracking with data association and track management.

In this paper, we consider a multiobject tracking problem in complex scenes. Unlike batch tracking systems using detections of the entire sequence, we propose a novel online multiobject tracking system in order to build tracks sequentially using online provided detections. To track objects robustly even under frequent occlusions, the proposed system consists of three main parts: 1) visual tracking with a novel data association with a track existence probability by associating online detections with the corresponding tracks under partial occlusions; 2) track management to associate terminated tracks for linking tracks fragmented by long-term occlusions; and 3) online model learning to generate discriminative appearance models for successful associations in other two parts.