Search Results for author:
Found 25 papers, 13 papers with code
SAFDNet: A Simple and Effective Network for Fully Sparse 3D Object Detection
LiDAR-based 3D object detection plays an essential role in autonomous driving.
DualTeacher: Bridging Coexistence of Unlabelled Classes for Semi-supervised Incremental Object Detection
A commonly-used strategy for supervised IOD is to encourage the current model (as a student) to mimic the behavior of the old model (as a teacher), but it generally fails in SSIOD because a dominant number of object instances from old and new classes are coexisting and unlabelled, with the teacher only recognizing a fraction of them.
InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image
With the success of Neural Radiance Field (NeRF) in 3D-aware portrait editing, a variety of works have achieved promising results regarding both quality and 3D consistency.
HEDNet: A Hierarchical Encoder-Decoder Network for 3D Object Detection in Point Clouds
To reduce computational costs, these methods resort to submanifold sparse convolutions, which prevent the information exchange among spatially disconnected features.
Self-Supervised Transformer with Domain Adaptive Reconstruction for General Face Forgery Video Detection
In this paper, a Self-supervised Transformer cooperating with Contrastive and Reconstruction learning (CoReST) is proposed, which is first pre-trained only on real face videos in a self-supervised manner, and then fine-tuned a linear head on specific face forgery video datasets.
PREIM3D: 3D Consistent Precise Image Attribute Editing from a Single Image
As for imprecise image editing, we attribute the problem to the gap between the latent space of real images and that of generated images.
CEDNet: A Cascade Encoder-Decoder Network for Dense Prediction
A hallmark of CEDNet is its ability to incorporate high-level features from early stages to guide low-level feature learning in subsequent stages, thereby enhancing the effectiveness of multi-scale feature fusion.
Infrared Invisible Clothing:Hiding from Infrared Detectors at Multiple Angles in Real World
We simulated the process from cloth to clothing in the digital world and then designed the adversarial "QR code" pattern.
AutoLoss-GMS: Searching Generalized Margin-Based Softmax Loss Function for Person Re-Identification
In this paper, we propose a novel method, AutoLoss-GMS, to search the better loss function in the space of generalized margin-based softmax loss function for person re-identification automatically.
Infrared Invisible Clothing: Hiding From Infrared Detectors at Multiple Angles in Real World
We simulated the process from cloth to clothing in the digital world and then designed the adversarial "QR code" pattern.
Attack on practical speaker verification system using universal adversarial perturbations
In authentication scenarios, applications of practical speaker verification systems usually require a person to read a dynamic authentication text.
Real-World Adversarial Attack
Room Impulse Response (RIR)
+3
RefineMask: Towards High-Quality Instance Segmentation with Fine-Grained Features
In this work, we propose a new method called RefineMask for high-quality instance segmentation of objects and scenes, which incorporates fine-grained features during the instance-wise segmenting process in a multi-stage manner.
Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation
Tremendous efforts have been made on instance segmentation but the mask quality is still not satisfactory.
Rethinking Natural Adversarial Examples for Classification Models
A detection model based on the classification model EfficientNet-B7 achieved a top-1 accuracy of 53. 95%, surpassing previous state-of-the-art classification models trained on ImageNet, suggesting that accurate localization information can significantly boost the performance of classification models on ImageNet-A.
The MSR-Video to Text Dataset with Clean Annotations
We cleaned the MSR-VTT annotations by removing these problems, then tested several typical video captioning models on the cleaned dataset.
Fooling thermal infrared pedestrian detectors in real world using small bulbs
By using a combination method, we successfully hide from the visible light and infrared object detection systems at the same time.
Deep Template Matching for Pedestrian Attribute Recognition with the Auxiliary Supervision of Attribute-wise Keypoints
Pedestrian Attribute Recognition (PAR) has aroused extensive attention due to its important role in video surveillance scenarios.
Preliminary Design of a FADC Readout System for the Alpha/Beta Discrimination in a Large Area Plastic Scintillation Detector
This paper describes a FADC Readout system developed for the tap water $\alpha/\beta$ dose monitoring system which is based on EJ444 phoswich scintillation detector and wavelength shifting fiber readout.
Instrumentation and Detectors
Delving Deeper into the Decoder for Video Captioning
Video captioning is an advanced multi-modal task which aims to describe a video clip using a natural language sentence.
Pairwise Teacher-Student Network for Semi-Supervised Hashing
Hashing method maps similar high-dimensional data to binary hashcodes with smaller hamming distance, and it has received broad attention due to its low storage cost and fast retrieval speed.
Factorized Distillation: Training Holistic Person Re-identification Model by Distilling an Ensemble of Partial ReID Models
Person re-identification (ReID) is aimed at identifying the same person across videos captured from different cameras.
Semantic Cluster Unary Loss for Efficient Deep Hashing
The resultant hashcodes form several compact clusters, which means hashcodes in the same cluster have similar semantic information.
Scalable Discrete Supervised Hash Learning with Asymmetric Matrix Factorization
Hashing method maps similar data to binary hashcodes with smaller hamming distance, and it has received a broad attention due to its low storage cost and fast retrieval speed.
CNN Based Hashing for Image Retrieval
Along with data on the web increasing dramatically, hashing is becoming more and more popular as a method of approximate nearest neighbor search.
Super-Bit Locality-Sensitive Hashing
Sign-random-projection locality-sensitive hashing (SRP-LSH) is a probabilistic dimension reduction method which provides an unbiased estimate of angular similarity, yet suffers from the large variance of its estimation.
