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Found 72 papers, 24 papers with code
The CRECIL Corpus: a New Dataset for Extraction of Relations between Characters in Chinese Multi-party Dialogues
We describe a new freely available Chinese multi-party dialogue dataset for automatic extraction of dialogue-based character relationships.
Leveraging Large Self-Supervised Time-Series Models for Transferable Diagnosis in Cross-Aircraft Type Bleed Air System
To address these challenges, this paper presents a self-supervised learning-based foundation model that enables the transfer of diagnostic knowledge from mature aircraft (e. g., A320, A330) to newer ones (e. g., C919).
MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
In this work, we present MotionDreamer, a localized masked modeling paradigm designed to learn internal motion patterns from a given motion with arbitrary topology and duration.
Driving behavior recognition via self-discovery learning
Autonomous driving systems require a deep understanding of human driving behaviors to achieve higher intelligence and safety. Despite advancements in deep learning, challenges such as long-tail distribution due to scarce samples and confusion from similar behaviors hinder effective driving behavior detection. Existing methods often fail to address sample confusion adequately, as datasets frequently contain ambiguous samples that obscure unique semantic information.
SuperNeRF-GAN: A Universal 3D-Consistent Super-Resolution Framework for Efficient and Enhanced 3D-Aware Image Synthesis
However, the high computational cost of NeRF presents challenges for synthesizing high-resolution (HR) images.
SLAM: Towards Efficient Multilingual Reasoning via Selective Language Alignment
Despite the significant improvements achieved by large language models (LLMs) in English reasoning tasks, these models continue to struggle with multilingual reasoning.
Efficient and Scalable Deep Reinforcement Learning for Mean Field Control Games
Building on previous works, We reformulate the infinite-agent stochastic control problem as a Markov Decision Process, where each representative agent interacts with the evolving mean field distribution.
BioTD: an online database of biotoxins
Biotoxins, mainly produced by venomous animals, plants and microorganisms, exhibit high physiological activity and unique effects such as lowering blood pressure and analgesia.
An Ensemble Approach to Short-form Video Quality Assessment Using Multimodal LLM
The rise of short-form videos, characterized by diverse content, editing styles, and artifacts, poses substantial challenges for learning-based blind video quality assessment (BVQA) models.
UniReal: Universal Image Generation and Editing via Learning Real-world Dynamics
We introduce UniReal, a unified framework designed to address various image generation and editing tasks.
FINECAPTION: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity
To support this endeavor, we introduce COMPOSITIONCAP, a new dataset for multi-grained region compositional image captioning, which introduces the task of compositional attribute-aware regional image captioning.
RegionGrasp: A Novel Task for Contact Region Controllable Hand Grasp Generation
This motivates us to consider a novel task of \textit{Region Controllable Hand Grasp Generation (RegionGrasp)}, as follows: given as input a 3D object, together with its specific surface area selected as the intended contact region, to generate a diverse set of plausible hand grasps of the object, where the thumb finger tip touches the object surface on the contact region.
RmGPT: Rotating Machinery Generative Pretrained Model
Extensive experiments demonstrate that RmGPT significantly outperforms state-of-the-art algorithms, achieving near-perfect accuracy in diagnosis tasks and exceptionally low errors in prognosis tasks.
GSD: View-Guided Gaussian Splatting Diffusion for 3D Reconstruction
We present GSD, a diffusion model approach based on Gaussian Splatting (GS) representation for 3D object reconstruction from a single view.
Improving Autoregressive Training with Dynamic Oracles
Many tasks within NLP can be framed as sequential decision problems, ranging from sequence tagging to text generation.
OmniControlNet: Dual-stage Integration for Conditional Image Generation
We provide a two-way integration for the widely adopted ControlNet by integrating external condition generation algorithms into a single dense prediction method and incorporating its individually trained image generation processes into a single model.
YouTube SFV+HDR Quality Dataset
We provided a comprehensive analysis of subjective quality scores for Short form SDR and HDR videos, and discuss the reliability of state-of-the-art UGC quality metrics and potential improvements.
FilterPrompt: A Simple yet Efficient Approach to Guide Image Appearance Transfer in Diffusion Models
Achieving this requires the effective decoupling of key attributes within the input image data to achieve representations accurately.
SwapAnything: Enabling Arbitrary Object Swapping in Personalized Visual Editing
Compared with existing methods for personalized subject swapping, SwapAnything has three unique advantages: (1) precise control of arbitrary objects and parts rather than the main subject, (2) more faithful preservation of context pixels, (3) better adaptation of the personalized concept to the image.
KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion
Previous methods for KGC re-ranking are mostly built on non-generative language models to obtain the probability of each candidate.
Bayesian Diffusion Models for 3D Shape Reconstruction
We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-up (data-driven) procedure via joint diffusion processes.
UniHuman: A Unified Model for Editing Human Images in the Wild
In this paper, we propose UniHuman, a unified model that addresses multiple facets of human image editing in real-world settings.
Learning Mutually Informed Representations for Characters and Subwords
In this paper, we introduce the entanglement model, aiming to combine character and subword language models.
Dolfin: Diffusion Layout Transformers without Autoencoder
In this paper, we introduce a novel generative model, Diffusion Layout Transformers without Autoencoder (Dolfin), which significantly improves the modeling capability with reduced complexity compared to existing methods.
Quantum-Enhanced Forecasting: Leveraging Quantum Gramian Angular Field and CNNs for Stock Return Predictions
We propose a time series forecasting method named Quantum Gramian Angular Field (QGAF).
Scalable Optimal Margin Distribution Machine
Optimal margin Distribution Machine (ODM) is a newly proposed statistical learning framework rooting in the novel margin theory, which demonstrates better generalization performance than the traditional large margin based counterparts.
LightPainter: Interactive Portrait Relighting with Freehand Scribble
Recent portrait relighting methods have achieved realistic results of portrait lighting effects given a desired lighting representation such as an environment map.
MRET: Multi-resolution Transformer for Video Quality Assessment
No-reference video quality assessment (NR-VQA) for user generated content (UGC) is crucial for understanding and improving visual experience.
IDM-Follower: A Model-Informed Deep Learning Method for Long-Sequence Car-Following Trajectory Prediction
Model-based and learning-based methods are two major types of methodologies to model car following behaviors.
CONVIQT: Contrastive Video Quality Estimator
Perceptual video quality assessment (VQA) is an integral component of many streaming and video sharing platforms.
Ranked #1 on
Video Quality Assessment
on LIVE-ETRI
(using extra training data)
On the Role of Generalization in Transferability of Adversarial Examples
We support our theoretical results by performing several numerical experiments showing the role of the substitute network's generalization in generating transferable adversarial examples.
Making Video Quality Assessment Models Sensitive to Frame Rate Distortions
We consider the problem of capturing distortions arising from changes in frame rate as part of Video Quality Assessment (VQA).
A Video Anomaly Detection Framework based on Appearance-Motion Semantics Representation Consistency
Firstly, we design a two-stream encoder to encode the appearance and motion information representations of normal samples and introduce constraints to further enhance the consistency of the feature semantics between appearance and motion information of normal samples so that abnormal samples with low consistency appearance and motion feature representation can be identified.
Ranked #2 on
Anomaly Detection
on CUHK Avenue
Perceptual Quality Assessment of UGC Gaming Videos
In recent years, with the vigorous development of the video game industry, the proportion of gaming videos on major video websites like YouTube has dramatically increased.
Subjective and Objective Analysis of Streamed Gaming Videos
A number of studies have been directed towards understanding the perceptual characteristics of professionally generated gaming videos arising in gaming video streaming, online gaming, and cloud gaming.
Interactive Portrait Harmonization
To enable flexible interaction between user and harmonization, we introduce interactive harmonization, a new setting where the harmonization is performed with respect to a selected \emph{region} in the reference image instead of the entire background.
Lite Vision Transformer with Enhanced Self-Attention
We propose Lite Vision Transformer (LVT), a novel light-weight transformer network with two enhanced self-attention mechanisms to improve the model performances for mobile deployment.
Image Quality Assessment using Contrastive Learning
We consider the problem of obtaining image quality representations in a self-supervised manner.
Ranked #2 on
Video Quality Assessment
on LIVE-ETRI
(using extra training data)
Distributed Optimal Margin Distribution Machine
Optimal margin Distribution Machine (ODM), a newly proposed statistical learning framework rooting in the novel margin theory, demonstrates better generalization performance than the traditional large margin based counterparts.
High Frame Rate Video Quality Assessment using VMAF and Entropic Differences
In this work we address the problem of frame rate dependent Video Quality Assessment (VQA) when the videos to be compared have different frame rate and compression factor.
Ranked #2 on
Video Quality Assessment
on LIVE-YT-HFR
SSH: A Self-Supervised Framework for Image Harmonization
Image harmonization aims to improve the quality of image compositing by matching the "appearance" (\eg, color tone, brightness and contrast) between foreground and background images.
MUSIQ: Multi-scale Image Quality Transformer
To accommodate this, the input images are usually resized and cropped to a fixed shape, causing image quality degradation.
Ranked #3 on
Image Quality Assessment
on MSU NR VQA Database
Rich Features for Perceptual Quality Assessment of UGC Videos
Besides the subjective ratings and content labels of the dataset, we also propose a DNN-based framework to thoroughly analyze importance of content, technical quality, and compression level in perceptual quality.
Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning
In this paper, we propose a generic model transfer scheme to make Convlutional Neural Networks (CNNs) interpretable, while maintaining their high classification accuracy.
Multimodal Contrastive Training for Visual Representation Learning
We first train our model on COCO and evaluate the learned visual representations on various downstream tasks including image classification, object detection, and instance segmentation.
Classifying Video based on Automatic Content Detection Overview
Video classification and analysis is always a popular and challenging field in computer vision.
Regression or Classification? New Methods to Evaluate No-Reference Picture and Video Quality Models
Video and image quality assessment has long been projected as a regression problem, which requires predicting a continuous quality score given an input stimulus.
RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content
However, these models are either incapable or inefficient for predicting the quality of complex and diverse UGC videos in practical applications.
Ranked #4 on
Video Quality Assessment
on LIVE Livestream
Electronic Correlations and Absence of Superconductivity in the Collapsed Phase of LaFe$_2$As$_2$
Our results indicate that the electronic structures of LaFe$_2$As$_2$ and CaFe$_2$As$_2$ are not too different, which further suggest that superconductivity might also be induced in the collapsed phase of LaFe$_2$As$_2$ under similar non-hydrostatic conditions as for CaFe$_2$As$_2$.
Strongly Correlated Electrons Superconductivity
Mask Guided Matting via Progressive Refinement Network
We propose Mask Guided (MG) Matting, a robust matting framework that takes a general coarse mask as guidance.
The Loewner-Kufarev Energy and Foliations by Weil-Petersson Quasicircles
Moreover, if either of these two energies is finite they are equal up to a constant factor, and in this case, the foliation leaves are Weil-Petersson quasicircles.
Complex Variables Mathematical Physics Mathematical Physics Probability
An Overview Of 3D Object Detection
Point cloud 3D object detection has recently received major attention and becomes an active research topic in 3D computer vision community.
ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction
We consider the problem of conducting frame rate dependent video quality assessment (VQA) on videos of diverse frame rates, including high frame rate (HFR) videos.
Ranked #1 on
Video Quality Assessment
on LIVE-YT-HFR
A Feasible Level Proximal Point Method for Nonconvex Sparse Constrained Optimization
We also establish new convergence complexities to achieve an approximate KKT solution when the objective can be smooth/nonsmooth, deterministic/stochastic and convex/nonconvex with complexity that is on a par with gradient descent for unconstrained optimization problems in respective cases.
Adaptive Debanding Filter
Banding artifacts, which manifest as staircase-like color bands on pictures or video frames, is a common distortion caused by compression of low-textured smooth regions.
Shape Adaptor: A Learnable Resizing Module
We present a novel resizing module for neural networks: shape adaptor, a drop-in enhancement built on top of traditional resizing layers, such as pooling, bilinear sampling, and strided convolution.
Subjective and Objective Quality Assessment of High Frame Rate Videos
We also conducted a holistic evaluation of existing state-of-the-art Full and No-Reference video quality algorithms, and statistically benchmarked their performance on the new database.
Incorporating Reinforced Adversarial Learning in Autoregressive Image Generation
To our best knowledge, the proposed method is first to enable adversarial learning in autoregressive models for image generation.
GIFnets: Differentiable GIF Encoding Framework
DitherNet manipulates the input image to reduce color banding artifacts and provides an alternative to traditional dithering.
Capturing Video Frame Rate Variations via Entropic Differencing
High frame rate videos are increasingly getting popular in recent years, driven by the strong requirements of the entertainment and streaming industries to provide high quality of experiences to consumers.
Ranked #3 on
Video Quality Assessment
on LIVE-YT-HFR
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
Recent years have witnessed an explosion of user-generated content (UGC) videos shared and streamed over the Internet, thanks to the evolution of affordable and reliable consumer capture devices, and the tremendous popularity of social media platforms.
Ranked #13 on
Video Quality Assessment
on LIVE-FB LSVQ
BBAND Index: A No-Reference Banding Artifact Predictor
Banding artifact, or false contouring, is a common video compression impairment that tends to appear on large flat regions in encoded videos.
YouTube UGC Dataset for Video Compression Research
However, traditional metrics used in compression and quality assessment, like BD-Rate and PSNR, are designed for pristine originals.
Multimedia Image and Video Processing
Multimodal Style Transfer via Graph Cuts
An assumption widely used in recent neural style transfer methods is that image styles can be described by global statics of deep features like Gram or covariance matrices.
Generalizing Graph Matching beyond Quadratic Assignment Model
Graph matching has received persistent attention over decades, which can be formulated as a quadratic assignment problem (QAP).
Improving Vision-based Self-positioning in Intelligent Transportation Systems via Integrated Lane and Vehicle Detection
In the framework, the number of lanes, the vehicle's position in those lanes and the presence of other vehicles are considered as parameters.
Hierarchical Attention Network for Action Recognition in Videos
Understanding human actions in wild videos is an important task with a broad range of applications.
PPP: Joint Pointwise and Pairwise Image Label Prediction
However, pointwise labels in image classification and tag annotation are inherently related to the pairwise labels.
Unsupervised Video Analysis Based on a Spatiotemporal Saliency Detector
Recently, the spectrum analysis based visual saliency approach has attracted a lot of interest due to its simplicity and good performance, where the phase information of the image is used to construct the saliency map.
Stereo under Sequential Optimal Sampling: A Statistical Analysis Framework for Search Space Reduction
We develop a sequential optimal sampling framework for stereo disparity estimation by adapting the Sequential Probability Ratio Test (SPRT) model.
