arXiv subjects

Bo Xiong

Publications and source records attributed to Bo Xiong.

At least 91 records · Page 5Linked to original sources

arXiv2021

Multiview Pseudo-Labeling for Semi-supervised Learning from Video

We present a multiview pseudo-labeling approach to video learning, a novel framework that uses complementary views in the form of appearance and motion information for semi-supervised learning in video. The complementary views help obtain more reliable pseudo-labels on unlabeled video, to learn stronger video representations than from purely supervised data. Though our method capitalizes on multiple views, it nonetheless trains a model that is shared across appearance and motion input and thus, by design, incurs no additional computation overhead at inference time. On multiple video recognition datasets, our method substantially outperforms its supervised counterpart, and compares favorably to previous work on standard benchmarks in self-supervised video representation learning.

cs.CV↗

arXiv2020

Quantum reflection of a Bose-Einstein condensate from a rapidly varying potential: the role of dark soliton

We study the dynamic behavior of a Bose-Einstein condensate (BEC) containing a dark soliton separately reflected from potential drops and potential barriers. It is shown that for a rapidly varying potential and in a certain regime of incident velocity, the quantum reflection probability displays the cosine of the deflection angle between the incident soliton and the reflected soliton, i.e., $R(θ) \sim \cos 2θ$. For a potential drop, $R(θ)$ is susceptible to the widths of potential drop up to the length of the dark soliton and the difference of the reflection rates between the orientation angle of the soliton $θ=0$ and $θ=π/2$, $δR_s$, displays oscillating exponential decay with increasing potential widths. However, for a barrier potential, $R(θ)$ is insensitive for the potential width less than the decay length of the matter wave and $δR_s$ presents an exponential trend. This discrepancy of the reflectances in two systems is arisen from the different behaviors of matter waves in the region of potential variation.

cond-mat.quant-gas↗

arXiv2019

Controllable splitting dynamics of a doubly quantized vortex in a rotating ring-shaped condensate

We study the dynamics of a doubly quantized vortex (DQV), created by releasing a ring-shaped Bose-Einstein condensate with quantized circulation into harmonic potential traps. It is shown that a DQV can be generated and exists stably in the middle of the ring-shaped condensate with the initial circulation $s = 2$ after released into the rotationally symmetric trap potential. For an asymmetric trap with a small degree of anisotropy the DQV initially splits into two singly quantized vortices and revives again but eventually evolves into two unit vortices due to the dynamic instability. For the degree of anisotropy above a critical value, the DQV is extremely unstably and decays rapidly into two singlet vortices. The geometry-dependent lifetime of the DQV and vortex-induced excitations are also discussed intensively.

cond-mat.quant-gas↗

arXiv2019

Less is More: Learning Highlight Detection from Video Duration

Highlight detection has the potential to significantly ease video browsing, but existing methods often suffer from expensive supervision requirements, where human viewers must manually identify highlights in training videos. We propose a scalable unsupervised solution that exploits video duration as an implicit supervision signal. Our key insight is that video segments from shorter user-generated videos are more likely to be highlights than those from longer videos, since users tend to be more selective about the content when capturing shorter videos. Leveraging this insight, we introduce a novel ranking framework that prefers segments from shorter videos, while properly accounting for the inherent noise in the (unlabeled) training data. We use it to train a highlight detector with 10M hashtagged Instagram videos. In experiments on two challenging public video highlight detection benchmarks, our method substantially improves the state-of-the-art for unsupervised highlight detection.

cs.CV↗

arXiv2018

Pixel Objectness: Learning to Segment Generic Objects Automatically in Images and Videos

We propose an end-to-end learning framework for segmenting generic objects in both images and videos. Given a novel image or video, our approach produces a pixel-level mask for all "object-like" regions---even for object categories never seen during training. We formulate the task as a structured prediction problem of assigning an object/background label to each pixel, implemented using a deep fully convolutional network. When applied to a video, our model further incorporates a motion stream, and the network learns to combine both appearance and motion and attempts to extract all prominent objects whether they are moving or not. Beyond the core model, a second contribution of our approach is how it leverages varying strengths of training annotations. Pixel-level annotations are quite difficult to obtain, yet crucial for training a deep network approach for segmentation. Thus we propose ways to exploit weakly labeled data for learning dense foreground segmentation. For images, we show the value in mixing object category examples with image-level labels together with relatively few images with boundary-level annotations. For video, we show how to bootstrap weakly annotated videos together with the network trained for image segmentation. Through experiments on multiple challenging image and video segmentation benchmarks, our method offers consistently strong results and improves the state-of-the-art for fully automatic segmentation of generic (unseen) objects. In addition, we demonstrate how our approach benefits image retrieval and image retargeting, both of which flourish when given our high-quality foreground maps. Code, models, and videos are at:http://vision.cs.utexas.edu/projects/pixelobjectness/

cs.CV↗

arXiv2018

Influence of a dark-soliton on the reflection of a Bose-Einstein condensate by a square barrier

We study the quantum reflection of a two-dimensional disk-shaped Bose-Einstein condensate with a dark-soliton excitation by a square potential barrier. For the giving geometry, the dark-soliton initially located at the centre of the condensate cloud survive long enough for investigating the reflection process. We show the time evolution of the reflection probability with respect to various width of the barrier. The asymptotic value of the reflection probability is decreased by the existence of a dark-soliton, and is highly sensitive to the initial orientation of the dark-soliton which also affects the excitation properties during the process of condensate and barrier interaction.

cond-mat.quant-gas↗

arXiv2018

Snap Angle Prediction for 360$^{\circ}$ Panoramas

360$^{\circ}$ panoramas are a rich medium, yet notoriously difficult to visualize in the 2D image plane. We explore how intelligent rotations of a spherical image may enable content-aware projection with fewer perceptible distortions. Whereas existing approaches assume the viewpoint is fixed, intuitively some viewing angles within the sphere preserve high-level objects better than others. To discover the relationship between these optimal snap angles and the spherical panorama's content, we develop a reinforcement learning approach for the cubemap projection model. Implemented as a deep recurrent neural network, our method selects a sequence of rotation actions and receives reward for avoiding cube boundaries that overlap with important foreground objects. We show our approach creates more visually pleasing panoramas while using 5x less computation than the baseline.

cs.CV↗

arXiv2018

Anharmonicity-Induced Criticality of Collective Excitation in a Trapped Bose-Einstein Condensate

We investigate the low energy excitations of a dilute atomic Bose gas confined in a anharmonic trap interacting with repulsive forces. The dispersion law of both surface and compression modes are derived and analyzed for large numbers of atoms in the trap, which show two branches of excitation and appear a two critical value. For a upper limit, BEC can be unstable with respect to some specific collective excitation, while for the lower limit, the frequency of collective excitation under anharmonic influence can be effectively lower than that without anharmonicity. Our work reveals the key role played by the anharmonicity and interatomic forces which introduce a rich structure in the dynamic behavior of these new many-body systems.

cond-mat.quant-gas↗

arXiv2018

Im2Flow: Motion Hallucination from Static Images for Action Recognition

Existing methods to recognize actions in static images take the images at their face value, learning the appearances---objects, scenes, and body poses---that distinguish each action class. However, such models are deprived of the rich dynamic structure and motions that also define human activity. We propose an approach that hallucinates the unobserved future motion implied by a single snapshot to help static-image action recognition. The key idea is to learn a prior over short-term dynamics from thousands of unlabeled videos, infer the anticipated optical flow on novel static images, and then train discriminative models that exploit both streams of information. Our main contributions are twofold. First, we devise an encoder-decoder convolutional neural network and a novel optical flow encoding that can translate a static image into an accurate flow map. Second, we show the power of hallucinated flow for recognition, successfully transferring the learned motion into a standard two-stream network for activity recognition. On seven datasets, we demonstrate the power of the approach. It not only achieves state-of-the-art accuracy for dense optical flow prediction, but also consistently enhances recognition of actions and dynamic scenes.

cs.CV↗

arXiv2018

Quantum information metric of conical defect

A concept of measuring the quantum distance between two different quantum states which is called quantum information metric is presented. The holographic principle (AdS/CFT) suggests that the quantum information metric $G_{λλ}$ between perturbed state and unperturbed state in field theory has a dual description in the classical gravity. In this work we calculate the quantum information metric of a theory which is dual to a conical defect geometry and we show that it is $n$ times the one of its covering space. We also give a holographic check for our result in the gravity side. Meanwhile, it was argued that $G_{λλ}$ is dual to a codimension-one surface in spacetime and satisfies $G_{λλ}=n_{d}\cdot\mbox{Vol}(Σ_{max})/L^{d}$. We show that the coefficient $n_d$ for conical defect should be rescaled by $n^2$ from the one for AdS. A limit case of conical defect --- the massless BTZ black hole--- is also considered. We show that the quantum information metric of the massless BTZ black hole disagrees with the one obtained by taking the vanishing temperature limit in BTZ black hole. This provides a new arena in differiating the different phases between BTZ spacetime and its massless cousin.

hep-th↗

arXiv2017

Predicting Foreground Object Ambiguity and Efficiently Crowdsourcing the Segmentation(s)

We propose the ambiguity problem for the foreground object segmentation task and motivate the importance of estimating and accounting for this ambiguity when designing vision systems. Specifically, we distinguish between images which lead multiple annotators to segment different foreground objects (ambiguous) versus minor inter-annotator differences of the same object. Taking images from eight widely used datasets, we crowdsource labeling the images as "ambiguous" or "not ambiguous" to segment in order to construct a new dataset we call STATIC. Using STATIC, we develop a system that automatically predicts which images are ambiguous. Experiments demonstrate the advantage of our prediction system over existing saliency-based methods on images from vision benchmarks and images taken by blind people who are trying to recognize objects in their environment. Finally, we introduce a crowdsourcing system to achieve cost savings for collecting the diversity of all valid "ground truth" foreground object segmentations by collecting extra segmentations only when ambiguity is expected. Experiments show our system eliminates up to 47% of human effort compared to existing crowdsourcing methods with no loss in capturing the diversity of ground truths.

cs.CV↗

arXiv2017

Pixel Objectness

We propose an end-to-end learning framework for generating foreground object segmentations. Given a single novel image, our approach produces pixel-level masks for all "object-like" regions---even for object categories never seen during training. We formulate the task as a structured prediction problem of assigning foreground/background labels to all pixels, implemented using a deep fully convolutional network. Key to our idea is training with a mix of image-level object category examples together with relatively few images with boundary-level annotations. Our method substantially improves the state-of-the-art on foreground segmentation for ImageNet and MIT Object Discovery datasets. Furthermore, on over 1 million images, we show that it generalizes well to segment object categories unseen in the foreground maps used for training. Finally, we demonstrate how our approach benefits image retrieval and image retargeting, both of which flourish when given our high-quality foreground maps.

cs.CV↗

arXiv2017

FusionSeg: Learning to combine motion and appearance for fully automatic segmention of generic objects in videos

We propose an end-to-end learning framework for segmenting generic objects in videos. Our method learns to combine appearance and motion information to produce pixel level segmentation masks for all prominent objects in videos. We formulate this task as a structured prediction problem and design a two-stream fully convolutional neural network which fuses together motion and appearance in a unified framework. Since large-scale video datasets with pixel level segmentations are problematic, we show how to bootstrap weakly annotated videos together with existing image recognition datasets for training. Through experiments on three challenging video segmentation benchmarks, our method substantially improves the state-of-the-art for segmenting generic (unseen) objects. Code and pre-trained models are available on the project website.

cs.CV↗

arXiv2016

Spin-orbit-coupling-induced magnetic heterostructure in the bilayer Bose-Hubbard system

We investigate magnetic phase in the bilayer system of ultra-cold bosons in an optical lattice, which is involved with Raman-induced spin-orbit (SO) coupling and laser-assisted interlayer tunneling. It is shown that there exit a rich of spin textures such as hetero ferromagnet, heterochiral magnet, chiral magnet with interlayer antiferromagnet. In particular, heterochiral magnet induced by SO coupling occurs extremely rarely in real solid-state materials. We present detailed experimental setup of realizing such a model in cold atom system.

cond-mat.quant-gas↗

arXiv2015

Transient currents of a single molecular junction with a vibrational mode

By using a propagation scheme for current matrices and an auxiliary mode expansion method, we investigate the transient dynamics of a single molecular junction coupled with a vibrational mode. Our approach is based on the Anderson-Holstein model and the dressed tunneling approximation for the electronic self-energy in the polaronic regime. The time-dependent currents after a sudden switching on the tunneling to leads and an abrupt upward step bias pulse are calculated. We show that the strong electron-phonon interaction greatly influences the nonlinear response properties of the system, and gives rise to interesting characteristics on the time traces of transient currents.

cond-mat.mes-hall↗

arXiv2015

Nonadiabatic multichannel dynamics of a spin-orbit coupled condensate

We investigate the nonadiabatic dynamics of a driven spin-orbit-coupled Bose-Einstein condensate in both weak and strong driven force. It is shown that the standard Landau-Zener (LZ) tunneling fails in the regime of weak driven force and/or strong spin-orbital coupling, where the full nonadiabatic dynamics requires a new mechanism through multichannel effects. Beyond the semiclassical approach, our numerical and analytical results show an oscillating power-law decay in the quantum limit, different from the exponential decay in the semiclassical limit of the LZ effect. Furthermore, the condensate density profile is found to be dynamically fragmented by the multichannel effects and enhanced by interaction effects. Our work therefore provides a complete picture to understand the nonadiabatic dynamics of a spin-orbit coupled condensate, including various range of driven force and interaction effects through multichannel interference. The experimental indication of these nonadiabatic dynamics is also discussed.

cond-mat.quant-gas↗

arXiv2014

Full Counting Statistics of Electron Tunneling through Coherently Coupled Quantum Dots: Exchange Interaction Effect on Shot Noise

We investigate the zero-frequency shot noise of electronic tunneling through a single quantum dot (SQD) and coherently coupled quantum dots (CQD) taking into account the Coulomb interaction. Within Hartree-Fock approximation, the analytical expressions of current and zero-frequency shot noise are self-consistently derived in the framework of full counting statistics for the both systems. We demonstrate that the correction term of zero-frequency shot noise induced by the intradot Coulomb interaction is almost negligible compared to the noninteracting shot noise in a SQD, while in a CQD the interplay of the interdot coherence fluctuations and strong interdot Coulomb interaction can induce a super-Poissonian noise even in the symmetric case.

cond-mat.mes-hall↗

arXiv2014

Topological Condensate in an Interaction Induced Gauge Potential

We systematically investigate the ground state and elementary excitations of a Bose-Einstein Condensate with a synthetic vector potential, which is induced by the many-body effects and atom-light coupling. For a sufficiently strong inter-atom interaction, we find the condensate undergoes a Stoner-type ferromagnetic transition through the self-consistent coupling with the vector potential. For a weak interaction, the critical velocity of a supercurrent is found anisotropic due to the density fluctuations affecting the gauge field. We further analytically demonstrate the topological ground state with a coreless vortex ring in a 3D harmonic trap and a coreless vortex-antivortex pair in a 2D trap. The circulating persistent current is measurable in the time-of-flight experiment or in the dipolar oscillation through the violation of Kohn theorem.

cond-mat.quant-gas↗