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Found 54 papers, 15 papers with code
HRCA+: Advanced Multiple-choice Machine Reading Comprehension Method
The HRCA model updates the information learned from the previous relation-pair to the next relation-pair.
Lodge: A Coarse to Fine Diffusion Network for Long Dance Generation Guided by the Characteristic Dance Primitives
In contrast, the second-stage is the local diffusion, which parallelly generates detailed motion sequences under the guidance of the dance primitives and choreographic rules.
Ranked #1 on
Motion Synthesis
on FineDance
Revisiting Edge Perturbation for Graph Neural Network in Graph Data Augmentation and Attack
It can be categorized into two veins based on their effects on the performance of graph neural networks (GNNs), i. e., graph data augmentation and attack.
OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems
Notably, the best-performing model, GPT-4V, attains an average score of 17. 23% on OlympiadBench, with a mere 11. 28% in physics, highlighting the benchmark rigor and the intricacy of physical reasoning.
Navigating the Dual Facets: A Comprehensive Evaluation of Sequential Memory Editing in Large Language Models
Our in-depth study advocates more careful use of ME in real-world scenarios.
A Saliency Enhanced Feature Fusion based multiscale RGB-D Salient Object Detection Network
SEFF utilizes saliency maps of the neighboring scales to enhance the necessary features for fusing, resulting in more representative fused features.
TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understanding
Humans commonly work with multiple objects in daily life and can intuitively transfer manipulation skills to novel objects by understanding object functional regularities.
TeleChat Technical Report
Subsequently, the model undergoes fine-tuning to align with human preferences, following a detailed methodology that we describe.
Towards 6G Digital Twin Channel Using Radio Environment Knowledge Pool
The digital twin channel (DTC) is crucial for 6G wireless autonomous networks as it replicates the wireless channel fading states in 6G air interface transmissions.
Ins-HOI: Instance Aware Human-Object Interactions Recovery
To address this, we further propose a complementary training strategy that leverages synthetic data to introduce instance-level shape priors, enabling the disentanglement of occupancy fields for different instances.
Adapting Vision Transformer for Efficient Change Detection
Most change detection models based on vision transformers currently follow a "pretraining then fine-tuning" strategy.
C-NERF: Representing Scene Changes as Directional Consistency Difference-based NeRF
Our approach surpasses state-of-the-art 2D change detection and NeRF-based methods by a significant margin.
GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussians
We present GaussianAvatar, an efficient approach to creating realistic human avatars with dynamic 3D appearances from a single video.
SpeechAct: Towards Generating Whole-body Motion from Speech
Then, we regress the motion representation from the audio signal by a translation model employing our contrastive motion learning method.
How to Extend 3D GBSM to Integrated Sensing and Communication Channel with Sharing Feature?
The proposed approach can be summarized as follows: Firstly, an ISAC channel model is proposed, where shared and non-shared components are superimposed for both communication and sensing.
Enhancing Spoofing Speech Detection Using Rhythm Information
Current spoofing speech detection systems need more convincing evidence.
EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval
Artificial intelligence (AI) technologies should adhere to human norms to better serve our society and avoid disseminating harmful or misleading information, particularly in Conversational Information Retrieval (CIR).
Synthetic Speech Detection Based on Temporal Consistency and Distribution of Speaker Features
Based on these analyzes, an SSD method based on temporal consistency and distribution of speaker features is proposed.
The Impact of Silence on Speech Anti-Spoofing
First, the reasons for the impact are explored, including the proportion of silence duration and the content of silence.
Improving Short Utterance Anti-Spoofing with AASIST2
The modified Res2Net blocks can extract multi-scale features and improve the detection performance for speech of different durations, thus improving the short utterance evaluation performance.
One-Class Knowledge Distillation for Spoofing Speech Detection
The detection of spoofing speech generated by unseen algorithms remains an unresolved challenge.
You talk what you read: Understanding News Comment Behavior by Dispositional and Situational Attribution
Many news comment mining studies are based on the assumption that comment is explicitly linked to the corresponding news.
ProxyCap: Real-time Monocular Full-body Capture in World Space via Human-Centric Proxy-to-Motion Learning
For more accurate and physically plausible predictions in world space, our network is designed to learn human motions from a human-centric perspective, which enables the understanding of the same motion captured with different camera trajectories.
Ranked #208 on
3D Human Pose Estimation
on Human3.6M
DataAI-6G: A System Parameters Configurable Channel Dataset for AI-6G Research
A common and accurate dataset is essential for the research of AI communication.
Channel Measurement, Modeling, and Simulation for 6G: A Survey and Tutorial
Then, a survey of the progress of the 6G channel research regarding the above five promising technologies is presented in terms of the latest measurement campaigns, new characteristics, modeling methods, and research prospects.
UniEX: An Effective and Efficient Framework for Unified Information Extraction via a Span-extractive Perspective
We propose a new paradigm for universal information extraction (IE) that is compatible with any schema format and applicable to a list of IE tasks, such as named entity recognition, relation extraction, event extraction and sentiment analysis.
NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension
Named-entity recognition (NER) detects texts with predefined semantic labels and is an essential building block for natural language processing (NLP).
StyleAvatar: Real-time Photo-realistic Portrait Avatar from a Single Video
Results and experiments demonstrate the superiority of our method in terms of image quality, full portrait video generation, and real-time re-animation compared to existing facial reenactment methods.
CloSET: Modeling Clothed Humans on Continuous Surface with Explicit Template Decomposition
In this way, the clothing deformations are disentangled such that the pose-dependent wrinkles can be better learned and applied to unseen poses.
OASIS: Automated Assessment of Urban Pedestrian Paths at Scale
The inspection of the Public Right of Way (PROW) for accessibility barriers is necessary for monitoring and maintaining the built environment for communities' walkability, rollability, safety, active transportation, and sustainability.
APE: An Open and Shared Annotated Dataset for Learning Urban Pedestrian Path Networks
The process features the use of a multi-input segmentation network trained on our dataset to predict important classes in the pedestrian environment and then generate a connected pedestrian path network.
How to Extend 3D GBSM to RIS Cascade Channel with Non-ideal Phase Modulation?
In the modeling process, we consider the non-ideal phase modulation of the RIS element, so as to accurately characterize the dependence of its phase modulation on the incoming wave angle.
Capacity Analysis of Holographic MIMO Channels with Practical Constraints
However, the channel might not satisfy isotropic scattering because of generalized angle distributions, and the antenna gain is limited by the array aperture in reality.
SrTR: Self-reasoning Transformer with Visual-linguistic Knowledge for Scene Graph Generation
The execution efficiency of the one-stage scene graph generation approaches are quite high, which infer the effective relation between entity pairs using sparse proposal sets and a few queries.
Background-Mixed Augmentation for Weakly Supervised Change Detection
Change detection (CD) is to decouple object changes (i. e., object missing or appearing) from background changes (i. e., environment variations) like light and season variations in two images captured in the same scene over a long time span, presenting critical applications in disaster management, urban development, etc.
A Shared Cluster-based Stochastic Channel Model for Joint Communication and Sensing Systems
Then, a stochastic JCAS channel model is proposed to capture the sharing feature, where shared and non-shared clusters by the two channels are defined and superimposed.
Solving Math Word Problems via Cooperative Reasoning induced Language Models
This inspires us to develop a cooperative reasoning-induced PLM for solving MWPs, called Cooperative Reasoning (CoRe), resulting in a human-like reasoning architecture with system 1 as the generator and system 2 as the verifier.
Ranked #103 on
Arithmetic Reasoning
on GSM8K
Deepfake Detection System for the ADD Challenge Track 3.2 Based on Score Fusion
The overfitting of the model to the training set leads to extreme values of the scores and low correlation of the score distributions, which makes score fusion difficult.
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
We hope that this project will be the foundation of Chinese cognitive intelligence.
Language-aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification
Text information including extensive prior knowledge about land cover classes has been ignored in hyperspectral image classification (HSI) tasks.
Single-source Domain Expansion Network for Cross-Scene Hyperspectral Image Classification
Currently, cross-scene hyperspectral image (HSI) classification has drawn increasing attention.
Towards No.1 in CLUE Semantic Matching Challenge: Pre-trained Language Model Erlangshen with Propensity-Corrected Loss
This report describes a pre-trained language model Erlangshen with propensity-corrected loss, the No. 1 in CLUE Semantic Matching Challenge.
IDET: Iterative Difference-Enhanced Transformers for High-Quality Change Detection
Change detection (CD) aims to detect change regions within an image pair captured at different times, playing a significant role in diverse real-world applications.
PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images
To address these issues, we propose a Pyramidal Mesh Alignment Feedback (PyMAF) loop in our regression network for well-aligned human mesh recovery and extend it as PyMAF-X for the recovery of expressive full-body models.
Ranked #6 on
3D Human Pose Estimation
on AGORA
(using extra training data)
SASV Based on Pre-trained ASV System and Integrated Scoring Module
Based on the assumption that there is a correlation between anti-spoofing and speaker verification, a Total-Divide-Total integrated Spoofing-Aware Speaker Verification (SASV) system based on pre-trained automatic speaker verification (ASV) system and integrated scoring module is proposed and submitted to the SASV 2022 Challenge.
Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification
The IDE-block is used to characterize and aggregate the intradomain nonlocal relationships and the interdomain feature and distribution similarities are captured in the CSA-block.
Adversarial Training-Aided Time-Varying Channel Prediction for TDD/FDD Systems
In this paper, a time-varying channel prediction method based on conditional generative adversarial network (CPcGAN) is proposed for time division duplexing/frequency division duplexing (TDD/FDD) systems.
Lightweight Multi-person Total Motion Capture Using Sparse Multi-view Cameras
Overall, we propose the first light-weight total capture system and achieves fast, robust and accurate multi-person total motion capture performance.
Ranked #2 on
3D Multi-Person Pose Estimation
on Shelf
DeepMultiCap: Performance Capture of Multiple Characters Using Sparse Multiview Cameras
We propose DeepMultiCap, a novel method for multi-person performance capture using sparse multi-view cameras.
Rethinking Semantic Segmentation Evaluation for Explainability and Model Selection
Semantic segmentation is a prerequisite for this task since it maps contiguous regions of the same class as single entities.
4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras
Our method enables a realtime online motion capture system running at 30fps using 5 cameras on a 5-person scene.
Ranked #8 on
3D Multi-Person Pose Estimation
on Shelf
Incorporating Linguistic Constraints into Keyphrase Generation
Keyphrases, that concisely describe the high-level topics discussed in a document, are very useful for a wide range of natural language processing tasks.
Training Bit Fully Convolutional Network for Fast Semantic Segmentation
Fully convolutional neural networks give accurate, per-pixel prediction for input images and have applications like semantic segmentation.
An Open Source Testing Tool for Evaluating Handwriting Input Methods
This paper presents an open source tool for testing the recognition accuracy of Chinese handwriting input methods.
