arXiv subjects

Guanghui Ren

Publications and source records attributed to Guanghui Ren.

46 records · Page 3Linked to original sources

arXiv2022

Spatio-temporal isolator in lithium niobate on insulator

In this contribution, we simulate, design, and experimentally demonstrate an integrated optical isolator based on spatiotemporal modulation in the thin-film lithium niobate on insulator waveguide platform. We used two cascaded travelling wave phase modulators for spatiotemporal modulation and a ring resonator as a wavelength filter to suppress the sidebands of the reverse propagating light. This enabled us to achieve an isolation of 27 dB. The demonstrated suppression of the reverse propagating light makes such isolators suitable for the integration with III-V laser diodes and Erbium doped gain sections in the thin-film lithium niobate on insulator waveguide platform.

physics.optics↗

arXiv2022

Phase retrieval of programmable photonic integrated circuits based on an on-chip fractional-delay reference path

Programmable photonic integrated circuits (PICs), offering diverse signal processing functions within a single chip, are promising solutions for applications ranging from optical communications to artificial intelligence. While the scale and complexity of programmable PICs is increasing, the characterization, and thus calibration, of them becomes increasingly challenging. Here we demonstrate a phase retrieval method for programmable PICs using an on-chip fractional-delay reference path. The impulse response of the chip can be uniquely and precisely identified from only the insertion loss using a standard complex Fourier transform. We demonstrate our approach experimentally with a 4-tap finite-impulse-response chip. The results match well with expectations and verifies our approach as effective for individually determining the taps' weights without the need for additional ports and photodiodes.

physics.optics↗

arXiv2022

Recirculating Light Phase Modulator

High efficiency and a compact footprint are desired properties for electro-optic modulators. In this paper, we propose, theoretically investigate and experimentally demonstrate a recirculating phase modulator, which increases the modulation efficiency by modulating the optical field several times in a non-resonant waveguide structure. The 'recycling' of light is achieved by looping the optical path that exits the phase modulator back and coupling it to a higher order waveguide mode, which then repeats its passage through the phase modulator. By looping the light back twice, we were able to demonstrate a recirculating phase modulator that requires nine times lower power to generate the same modulation index of a single pass phase modulator. This approach of modulation efficiency enhancement is promising for the design of advanced tunable electro optical frequency comb generators and other electro-optical devices with defined operational frequency bandwidths.

physics.optics↗

arXiv2021

Improved Pillar with Fine-grained Feature for 3D Object Detection

3D object detection with LiDAR point clouds plays an important role in autonomous driving perception module that requires high speed, stability and accuracy. However, the existing point-based methods are challenging to reach the speed requirements because of too many raw points, and the voxel-based methods are unable to ensure stable speed because of the 3D sparse convolution. In contrast, the 2D grid-based methods, such as PointPillar, can easily achieve a stable and efficient speed based on simple 2D convolution, but it is hard to get the competitive accuracy limited by the coarse-grained point clouds representation. So we propose an improved pillar with fine-grained feature based on PointPillar that can significantly improve detection accuracy. It consists of two modules, including height-aware sub-pillar and sparsity-based tiny-pillar, which get fine-grained representation respectively in the vertical and horizontal direction of 3D space. For height-aware sub-pillar, we introduce a height position encoding to keep height information of each sub-pillar during projecting to a 2D pseudo image. For sparsity-based tiny-pillar, we introduce sparsity-based CNN backbone stacked by dense feature and sparse attention module to extract feature with larger receptive field efficiently. Experimental results show that our proposed method significantly outperforms previous state-of-the-art 3D detection methods on the Waymo Open Dataset. The related code will be released to facilitate the academic and industrial study.

cs.CV↗

arXiv2021

Human-centric Relation Segmentation: Dataset and Solution

Vision and language understanding techniques have achieved remarkable progress, but currently it is still difficult to well handle problems involving very fine-grained details. For example, when the robot is told to "bring me the book in the girl's left hand", most existing methods would fail if the girl holds one book respectively in her left and right hand. In this work, we introduce a new task named human-centric relation segmentation (HRS), as a fine-grained case of HOI-det. HRS aims to predict the relations between the human and surrounding entities and identify the relation-correlated human parts, which are represented as pixel-level masks. For the above exemplar case, our HRS task produces results in the form of relation triplets and exacts segmentation masks of the book, with which the robot can easily accomplish the grabbing task. Correspondingly, we collect a new Person In Context (PIC) dataset for this new task, which contains 17,122 high-resolution images and densely annotated entity segmentation and relations, including 141 object categories, 23 relation categories and 25 semantic human parts. We also propose a Simultaneous Matching and Segmentation (SMS) framework as a solution to the HRS task. I Outputs of the three branches are fused to produce the final HRS results. Extensive experiments on PIC and V-COCO datasets show that the proposed SMS method outperforms baselines with the 36 FPS inference speed.

cs.CV↗

arXiv2021

Video Relation Detection with Trajectory-aware Multi-modal Features

Video relation detection problem refers to the detection of the relationship between different objects in videos, such as spatial relationship and action relationship. In this paper, we present video relation detection with trajectory-aware multi-modal features to solve this task. Considering the complexity of doing visual relation detection in videos, we decompose this task into three sub-tasks: object detection, trajectory proposal and relation prediction. We use the state-of-the-art object detection method to ensure the accuracy of object trajectory detection and multi-modal feature representation to help the prediction of relation between objects. Our method won the first place on the video relation detection task of Video Relation Understanding Grand Challenge in ACM Multimedia 2020 with 11.74\% mAP, which surpasses other methods by a large margin.

cs.CV↗

arXiv2020

ProxylessKD: Direct Knowledge Distillation with Inherited Classifier for Face Recognition

Knowledge Distillation (KD) refers to transferring knowledge from a large model to a smaller one, which is widely used to enhance model performance in machine learning. It tries to align embedding spaces generated from the teacher and the student model (i.e. to make images corresponding to the same semantics share the same embedding across different models). In this work, we focus on its application in face recognition. We observe that existing knowledge distillation models optimize the proxy tasks that force the student to mimic the teacher's behavior, instead of directly optimizing the face recognition accuracy. Consequently, the obtained student models are not guaranteed to be optimal on the target task or able to benefit from advanced constraints, such as large margin constraints (e.g. margin-based softmax). We then propose a novel method named ProxylessKD that directly optimizes face recognition accuracy by inheriting the teacher's classifier as the student's classifier to guide the student to learn discriminative embeddings in the teacher's embedding space. The proposed ProxylessKD is very easy to implement and sufficiently generic to be extended to other tasks beyond face recognition. We conduct extensive experiments on standard face recognition benchmarks, and the results demonstrate that ProxylessKD achieves superior performance over existing knowledge distillation methods.

cs.CV↗

arXiv2019

Ridge Resonance: A new Resonance Phenomenon for Silicon Photonics Harnessing Bound States in the Continuum

We present a new resonant behavior based on bound states in the continuum in a guided wave silicon platform. The continuum has the form of a collimated beam of light which is confined vertically in a TE mode of a silicon slab. The bound state is a discrete TM mode of a ridge on the silicon slab. The coupling between the slab and ridge modes results in a single sharp resonance at the wavelength where they phase match. We experimentally demonstrate this phenomenon on a silicon photonic chip using foundry compatible parameters and interface it on-chip to standard single mode silicon nanowire waveguides. The fabricated chip exhibits a single sharp resonance near 1550 nm with a line width of a few nanometer, an extinction ratio of 25 dB and a thermal stability of 19.5 pm/C. We believe that this is the first demonstration of bound states in the continuum resonance realized using guided wave components.

physics.optics↗

arXiv2018

Cross-domain Human Parsing via Adversarial Feature and Label Adaptation

Human parsing has been extensively studied recently due to its wide applications in many important scenarios. Mainstream fashion parsing models focus on parsing the high-resolution and clean images. However, directly applying the parsers trained on benchmarks to a particular application scenario in the wild, e.g., a canteen, airport or workplace, often gives non-satisfactory performance due to domain shift. In this paper, we explore a new and challenging cross-domain human parsing problem: taking the benchmark dataset with extensive pixel-wise labeling as the source domain, how to obtain a satisfactory parser on a new target domain without requiring any additional manual labeling? To this end, we propose a novel and efficient cross-domain human parsing model to bridge the cross-domain differences in terms of visual appearance and environment conditions and fully exploit commonalities across domains. Our proposed model explicitly learns a feature compensation network, which is specialized for mitigating the cross-domain differences. A discriminative feature adversarial network is introduced to supervise the feature compensation to effectively reduce the discrepancy between feature distributions of two domains. Besides, our model also introduces a structured label adversarial network to guide the parsing results of the target domain to follow the high-order relationships of the structured labels shared across domains. The proposed framework is end-to-end trainable, practical and scalable in real applications. Extensive experiments are conducted where LIP dataset is the source domain and 4 different datasets including surveillance videos, movies and runway shows are evaluated as target domains. The results consistently confirm data efficiency and performance advantages of the proposed method for the cross-domain human parsing problem.

cs.CV↗

arXiv2017

Integrated Fabry-Perot cavities as a mechanism for enhancing micro-ring resonator performance

We propose and experimentally demonstrate the enhancement in the filtering quality (Q) factor of an integrated micro-ring resonator (MRR) by embedding it in an integrated Fabry-Perot (FP) cavity formed by cascaded Sagnac loop reflectors (SLRs). By utilizing coherent interference within the FP cavity to reshape the transmission spectrum of the MRR, both the Q factor and the extinction ratio (ER) can be significantly improved. The device is theoretically analyzed, and practically fabricated on a silicon-on-insulator (SOI) wafer. Experimental results show that up to 11-times improvement in Q factor, together with an 8-dB increase in ER, can be achieved via our proposed method. The impact of varying structural parameters on the device performance is also investigated and verified by the measured spectra of the fabricated devices with different structural parameters.

physics.optics↗