Object Detection in 20 Years: A Survey

Object detection, as of one the most fundamental and challenging problems in computer vision, has received great attention in recent years. Its development in the past two decades can be regarded as an epitome of computer vision history. If we think of today's object detection as a technical aesthetics under the power of deep learning, then turning back the clock 20 years we would witness the wisdom of cold weapon era. This paper extensively reviews 400+ papers of object detection in the light of its technical evolution, spanning over a quarter-century's time (from the 1990s to 2019). A number of topics have been covered in this paper, including the milestone detectors in history, detection datasets, metrics, fundamental building blocks of the detection system, speed up techniques, and the recent state of the art detection methods. This paper also reviews some important detection applications, such as pedestrian detection, face detection, text detection, etc, and makes an in-deep analysis of their challenges as well as technical improvements in recent years.Comment: This work has been submitted to the IEEE TPAMI for possible publicatio

Anomaly of (2+1)(2+1)-Dimensional Symmetry-Enriched Topological Order from (3+1)(3+1)-Dimensional Topological Quantum Field Theory

Symmetry acting on a (2+1)$D$ topological order can be anomalous in the sense that they possess an obstruction to being realized as a purely (2+1)$D$ on-site symmetry. In this paper, we develop a (3+1)$D$ topological quantum field theory to calculate the anomaly indicators of a (2+1)$D$ topological order with a general symmetry group $G$, which may be discrete or continuous, Abelian or non-Abelian, contain anti-unitary elements or not, and permute anyons or not. These anomaly indicators are partition functions of the (3+1)$D$ topological quantum field theory on a specific manifold equipped with some $G$-bundle, and they are expressed using the data characterizing the topological order and the symmetry actions. Our framework is applied to derive the anomaly indicators for various symmetry groups, including $\mathbb{Z}_2\times\mathbb{Z}_2$, $\mathbb{Z}_2^T\times\mathbb{Z}_2^T$, $SO(N)$, $O(N)^T$, $SO(N)\times \mathbb{Z}_2^T$, etc, where $\mathbb{Z}_2$ and $\mathbb{Z}_2^T$ denote a unitary and anti-unitary order-2 group, respectively, and $O(N)^T$ denotes a symmetry group $O(N)$ such that elements in $O(N)$ with determinant $-1$ are anti-unitary. In particular, we demonstrate that some anomaly of $O(N)^T$ and $SO(N)\times \mathbb{Z}_2^T$ exhibit symmetry-enforced gaplessness, i.e., they cannot be realized by any symmetry-enriched topological order. As a byproduct, for $SO(N)$ symmetric topological orders, we derive their $SO(N)$ Hall conductance.Comment: Recipe of calculating the partition function involving continuous symmetries added, together with extra example

On Development History of Australia’s Language Policy and the Enlightenment to China’s Foreign Language Education

As is well-known, Australia is the first English country to officially make and efficiently carry out multi-lingual and plural culture in the world, whose language education policy has been highly spoken of by most linguists and politicians in the world in terms of the formulation and implementation. By studying such items as affecting factors, development history, implementing strategies of Australian language education policy under the background of multiculturalism, researchers can get a clue of the law of development of the language education policy in the developed countries and even the world. To be specific, through studying the development history of Australian language education policy under the background of multiculturalism, the paper puts forward some enlightenment and presents some advice on the China’s foreign language education

Amplitude death in nonlinear oscillators with mixed time-delayed coupling

Peer reviewedPublisher PD

Application of Time-Fractional Order Bloch Equation in Magnetic Resonance Fingerprinting

Magnetic resonance fingerprinting (MRF) is one novel fast quantitative imaging framework for simultaneous quantification of multiple parameters with pseudo-randomized acquisition patterns. The accuracy of the resulting multi-parameters is very important for clinical applications. In this paper, we derived signal evolutions from the anomalous relaxation using a fractional calculus. More specifically, we utilized time-fractional order extension of the Bloch equations to generate dictionary to provide more complex system descriptions for MRF applications. The representative results of phantom experiments demonstrated the good accuracy performance when applying the time-fractional order Bloch equations to generate dictionary entries in the MRF framework. The utility of the proposed method is also validated by in-vivo study.Comment: Accepted at 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019

Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise

The existence of spurious correlations such as image backgrounds in the training environment can make empirical risk minimization (ERM) perform badly in the test environment. To address this problem, Kirichenko et al. (2022) empirically found that the core features that are related to the outcome can still be learned well even with the presence of spurious correlations. This opens a promising strategy to first train a feature learner rather than a classifier, and then perform linear probing (last layer retraining) in the test environment. However, a theoretical understanding of when and why this approach works is lacking. In this paper, we find that core features are only learned well when their associated non-realizable noise is smaller than that of spurious features, which is not necessarily true in practice. We provide both theories and experiments to support this finding and to illustrate the importance of non-realizable noise. Moreover, we propose an algorithm called Freeze then Train (FTT), that first freezes certain salient features and then trains the rest of the features using ERM. We theoretically show that FTT preserves features that are more beneficial to test time probing. Across two commonly used spurious correlation datasets, FTT outperforms ERM, IRM, JTT and CVaR-DRO, with substantial improvement in accuracy (by 4.5%) when the feature noise is large. FTT also performs better on general distribution shift benchmarks

Optical-pumping enantio-conversion of chiral mixtures in presence of tunneling between chiral states

Enantio-conversion of chiral mixtures, converting the mixtures composed of left- and right-handed chiral molecules into the homochiral ensembles, has become an important research topic in chemical and biological fields. In previous studies on enantio-conversion, the tunneling interaction between the left- and right-handed chiral states was often neglected. However, for certain chiral molecules, this tunneling interaction is significant and cannot be ignored. Here we propose a scheme for enantio-conversion of chiral mixtures through optical pumping based on a four-level model of chiral molecules, comprising two chiral ground states and two achiral excited states, with a tunneling interaction between the chiral states. Under one-photon large detuning and two-photon resonance conditions, one of the achiral excited states is eliminated adiabatically. By well designing the detuning and coupling strengths of the electromagnetic fields, the tunneling interaction between two chiral states and the interaction between one of the chiral states and the remaining achiral excited state can be eliminated. Consequently, one chiral state remains unchanged, while the other can be excited to an achiral excited state, establishing chiral-state-selective excitations. By numerically calculating the populations of two chiral ground states and the enantiomeric excess, we observe that high-efficiency enantio-conversion is achieved under the combined effects of system dissipation and chiral-state-selective excitations.Comment: 14 pages, 6 figure