Search Results for author:
Found 32 papers, 15 papers with code
AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation
In this paper, we propose an adaptive weighting regression (AWR) method to leverage the advantages of both detection-based and regression-based methods.
Ranked #1 on
Hand Pose Estimation
on HANDS 2017
Decoupled Iterative Refinement Framework for Interacting Hands Reconstruction from a Single RGB Image
On the other hand, there are complex spatial relationship between interacting hands, which significantly increases the solution space of hand poses and increases the difficulty of network learning.
Ranked #3 on
3D Interacting Hand Pose Estimation
on InterHand2.6M
HaMuCo: Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning
Recent advancements in 3D hand pose estimation have shown promising results, but its effectiveness has primarily relied on the availability of large-scale annotated datasets, the creation of which is a laborious and costly process.
Can Shuffling Video Benefit Temporal Bias Problem: A Novel Training Framework for Temporal Grounding
Our framework introduces two auxiliary tasks, cross-modal matching and temporal order discrimination, to promote the grounding model training.
OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks
Many channel pruning works utilize structured sparsity regularization to zero out all the weights in some channels and automatically obtain structure-sparse network in training stage.
Interpretable Online Log Analysis Using Large Language Models with Prompt Strategies
LogPrompt employs large language models (LLMs) to perform online log analysis tasks via a suite of advanced prompt strategies tailored for log tasks, which enhances LLMs' performance by up to 380. 7% compared with simple prompts.
Multi-Level Aggregation and Recursive Alignment Architecture for Efficient Parallel Inference Segmentation Network
Real-time semantic segmentation is a crucial research for real-world applications.
How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?
It shows that finetuning PLMs with diffusion degrades the reconstruction ability on OOD data.
Approximation of Images via Generalized Higher Order Singular Value Decomposition over Finite-dimensional Commutative Semisimple Algebra
Higher order singular value decomposition (HOSVD) extends the SVD and can approximate higher order data using sums of a few rank-one components.
Mining Multi-View Information: A Strong Self-Supervised Framework for Depth-Based 3D Hand Pose and Mesh Estimation
However, these methods ignore the rich semantic information in each view and ignore the complex dependencies between different regions of different views.
Automatic Generation of Topology Diagrams for Strongly-Meshed Power Transmission Systems
This paper proposes an integrated framework for generating aesthetically-pleasing topology diagrams for power transmission systems.
A Comprehensive End-to-End Computer Vision Framework for Restoration and Recognition of Low-Quality Engineering Drawings
Existing computer vision approaches for digitizing engineering drawings typically assume the input drawings have high quality.
Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decoding
However, the decoding process in EA - essential for effective operation and alignment accuracy - has received limited attention and remains tailored to specific datasets and model architectures, necessitating both entity and additional explicit relation embeddings.
Towards Semantic Consistency: Dirichlet Energy Driven Robust Multi-Modal Entity Alignment
This study introduces a novel approach, DESAlign, which addresses these issues by applying a theoretical framework based on Dirichlet energy to ensure semantic consistency.
Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation
In this paper, we present a propagation perspective to analyze weakly supervised EA and explain the existing aggregation-based EA models.
Chinese/English mixed Character Segmentation as Semantic Segmentation
We take advantage of the successful architecture called fully convolutional networks (FCN) in the field of semantic segmentation.
Investigating Capsule Network and Semantic Feature on Hyperplanes for Text Classification
It has been demonstrated that multiple senses of a word actually reside in linear superposition within the word embedding so that specific senses can be extracted from the original word embedding.
Capsule Network with Interactive Attention for Aspect-Level Sentiment Classification
Aspect-level sentiment classification is a crucial task for sentiment analysis, which aims to identify the sentiment polarities of specific targets in their context.
Fewer is More: Image Segmentation Based Weakly Supervised Object Detection with Partial Aggregation
As most weakly supervised object detection methods are based on pre-generated proposals, they often show two false detections: (i) group multiple object instances with one bounding box, and (ii) focus on only parts rather than the whole objects.
Ranked #25 on
Weakly Supervised Object Detection
on PASCAL VOC 2007
Towards automatic visual inspection: A weakly supervised learning method for industrial applicable object detection
With the recent progress of deep learning, advanced industrial object detectors are built for smart industrial applications.
Ranked #22 on
Weakly Supervised Object Detection
on PASCAL VOC 2007
Adversarial and Domain-Aware BERT for Cross-Domain Sentiment Analysis
To tackle these problems, we design a post-training procedure, which contains the target domain masked language model task and a novel domain-distinguish pre-training task.
Robust Unsupervised Video Anomaly Detection by Multi-Path Frame Prediction
In this paper, we propose a novel and robust unsupervised video anomaly detection method by frame prediction with proper design which is more in line with the characteristics of surveillance videos.
CAP-RAM: A Charge-Domain In-Memory Computing 6T-SRAM for Accurate and Precision-Programmable CNN Inference
A compact, accurate, and bitwidth-programmable in-memory computing (IMC) static random-access memory (SRAM) macro, named CAP-RAM, is presented for energy-efficient convolutional neural network (CNN) inference.
Modeling Aspect Correlation for Aspect-based Sentiment Analysis via Recurrent Inverse Learning Guidance
Second, we propose Inverse Learning Guidance to improve the selection of aspect feature by considering aspect correlation, which provides more useful information to determine polarity.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Universal adaptive optics for microscopy through embedded neural network control
Unlike previous ML methods, we used a bespoke neural network (NN) architecture, designed using physical understanding of image formation, that was embedded in the control loop of the microscope.
Question-Driven Span Labeling Model for Aspect–Opinion Pair Extraction
Specifically, we divide the AOPE task into aspect term extraction (ATE) and aspect-specified opinion extraction (ASOE) subtasks; we first extract all the candidate aspect terms and then the corresponding opinion words given the aspect term.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
Adaptive DNN Surgery for Selfish Inference Acceleration with On-demand Edge Resource
Deep Neural Networks (DNNs) have significantly improved the accuracy of intelligent applications on mobile devices.
Extracting Physical Causality from Measurements to Detect and Localize False Data Injection Attacks
They are sensitive to the violation of physical laws caused by FDIA, but tend to remain stable with the drift of system operating points.
Improved Efficient Two-Stage Denoising Diffusion Power System Measurement Recovery Against False Data Injection Attacks and Data Losses
Fortunately, the powerful generation ability of the denoising diffusion models can enable more precise measurement generation for power system data recovery.
An Order-Complexity Aesthetic Assessment Model for Aesthetic-aware Music Recommendation
In order to improve the quality of AI music generation and further guide computer music production, synthesis, recommendation and other tasks, we use Birkhoff's aesthetic measure to design a aesthetic model, objectively measuring the aesthetic beauty of music, and form a recommendation list according to the aesthetic feeling of music.
Object-level Copy-Move Forgery Image Detection based on Inconsistency Mining
Additionally, we extract inconsistent regions between coarse similar regions obtained through self-correlation calculations and regions composed of prototypes.
MLS-Track: Multilevel Semantic Interaction in RMOT
The new trend in multi-object tracking task is to track objects of interest using natural language.
