Search Results for author:
Found 31 papers, 16 papers with code
RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusion
In this work, inspired by the stellar achievements of the diffusion model in CV and NLP, we adapt it to the RF domain and propose RF-Diffusion.
UniHDA: A Unified and Versatile Framework for Multi-Modal Hybrid Domain Adaptation
In this paper, we propose UniHDA, a \textbf{unified} and \textbf{versatile} framework for generative hybrid domain adaptation with multi-modal references from multiple domains.
TagCLIP: A Local-to-Global Framework to Enhance Open-Vocabulary Multi-Label Classification of CLIP Without Training
As a result, we dissect the preservation of patch-wise spatial information in CLIP and proposed a local-to-global framework to obtain image tags.
SmoothVideo: Smooth Video Synthesis with Noise Constraints on Diffusion Models for One-shot Video Tuning
By applying the loss to existing one-shot video tuning methods, we significantly improve the overall consistency and smoothness of the generated videos.
Pair-wise Layer Attention with Spatial Masking for Video Prediction
To this end, we present a Pair-wise Layer Attention with Spatial Masking (PLA-SM) framework for video prediction to capture the spatiotemporal dynamics, which reflect the motion trend.
Few-shot Hybrid Domain Adaptation of Image Generators
Concretely, the distance loss blends the attributes of all target domains by reducing the distances from generated images to all target subspaces.
NormKD: Normalized Logits for Knowledge Distillation
In this paper, we restudy the hyper-parameter temperature and figure out its incapability to distill the knowledge from each sample sufficiently when it is a single value.
Learning Occupancy for Monocular 3D Object Detection
Monocular 3D detection is a challenging task due to the lack of accurate 3D information.
APPT : Asymmetric Parallel Point Transformer for 3D Point Cloud Understanding
To tackle these problems, we propose Asymmetric Parallel Point Transformer (APPT).
Improving Multi-generation Robustness of Learned Image Compression
Benefit from flexible network designs and end-to-end joint optimization approach, learned image compression (LIC) has demonstrated excellent coding performance and practical feasibility in recent years.
DID-M3D: Decoupling Instance Depth for Monocular 3D Object Detection
Therefore, we propose to reformulate the instance depth to the combination of the instance visual surface depth (visual depth) and the instance attribute depth (attribute depth).
Dual Power Spectrum Manifold and Toeplitz HPD Manifold: Enhancement and Analysis for Matrix CFAR Detection
These advantages benefit from the geometry of the Toeplitz Hermitian positive definite (HPD) manifold $\mathcal{M}_{\mathcal{T}H_{++}}$, but the sophisticated geometry also results in some challenges for geometric detectors, such as the implementation of the enhanced detector to improve the SCR (signal-to-clutter ratio) and the analysis of the detection performance.
Hands-on Wireless Sensing with Wi-Fi: A Tutorial
With the rapid development of wireless communication technology, wireless access points (AP) and internet of things (IoT) devices have been widely deployed in our surroundings.
CLRNet: Cross Layer Refinement Network for Lane Detection
In this way, we can exploit more contextual information to detect lanes while leveraging local detailed lane features to improve localization accuracy.
Ranked #1 on
Lane Detection
on LLAMAS
WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection
This network is learned by minimizing our newly-proposed 3D alignment loss between the 3D box estimates and the corresponding RoI LiDAR points.
Lidar Point Cloud Guided Monocular 3D Object Detection
We delve into this underlying mechanism and then empirically find that: concerning the label accuracy, the 3D location part in the label is preferred compared to other parts of labels.
Suppress-and-Refine Framework for End-to-End 3D Object Detection
In this work, we propose a suppress-and-refine framework to remove these handcrafted components.
Optical isolation induced by subwavelength spinning particle via spin-orbit interaction
Optical isolation enables nonreciprocal manipulations of light with broad applications in optical communications.
Optics
Dynamic Phase Diagram of an Orthogonal Spin Torque device: Topological Category
The magnetization evolution of the free layer in an orthogonal spin-torque device is studied based on a macrospin model.
Mesoscale and Nanoscale Physics
RESA: Recurrent Feature-Shift Aggregator for Lane Detection
Lane detection is one of the most important tasks in self-driving.
Ranked #4 on
Lane Detection
on TuSimple
Gender Classification and Bias Mitigation in Facial Images
We worked to increase classification accuracy and mitigate algorithmic biases on our baseline model trained on the augmented benchmark database.
Boundary-Aware Dense Feature Indicator for Single-Stage 3D Object Detection from Point Clouds
3D object detection based on point clouds has become more and more popular.
PI-RCNN: An Efficient Multi-sensor 3D Object Detector with Point-based Attentive Cont-conv Fusion Module
Moreover, based on the PACF module, we propose a 3D multi-sensor multi-task network called Pointcloud-Image RCNN(PI-RCNN as brief), which handles the image segmentation and 3D object detection tasks.
Region Mutual Information Loss for Semantic Segmentation
In this paper, we develop a region mutual information (RMI) loss to model the dependencies among pixels more simply and efficiently.
Training-Time-Friendly Network for Real-Time Object Detection
Experiments on MS COCO show that our TTFNet has great advantages in balancing training time, inference speed, and accuracy.
Improving Semantic Segmentation via Dilated Affinity
To be specific, our method explicitly requires the network to predict semantic segmentation as well as dilated affinity, which is a sparse version of pair-wise pixel affinity.
Interpretable Parallel Recurrent Neural Networks with Convolutional Attentions for Multi-Modality Activity Modeling
Multimodal features play a key role in wearable sensor-based human activity recognition (HAR).
Lolisa: Formal syntax and semantics for a subset of the solidity programming language in Mathematical Tool Coq
This article presents the formal syntax and semantics for a large subset of the Solidity programming language developed for the Etheruem blockchain platform based on our resent work about developing a general, extensible, and reusable formal memory (GERM) framework and an extension of Curry-Howard isomorphism, denoted as execution-verification isomorphism (EVI).
Programming Languages
Exploration on Generating Traditional Chinese Medicine Prescription from Symptoms with an End-to-End method
Traditional Chinese Medicine (TCM) is an influential form of medical treatment in China and surrounding areas.
Distributed Representation for Traditional Chinese Medicine Herb via Deep Learning Models
Traditional Chinese Medicine (TCM) has accumulated a big amount of precious resource in the long history of development.
DeepKey: An EEG and Gait Based Dual-Authentication System
Biometric authentication involves various technologies to identify individuals by exploiting their unique, measurable physiological and behavioral characteristics.
