Papers Relation Network
“Relation Network” 태그가 달린 논문 123편 · 필터 해제
FDDet: Frequency-Decoupling for Boundary Refinement in Temporal Action Detection
Temporal action detection aims to locate and classify actions in untrimmed videos. While recent works focus on designing powerful feature processors for pre-trained representations, they often overlook the inherent noise…
Action DetectionRelation NetworkUnraveling the geometry of visual relational reasoning
Humans and other animals readily generalize abstract relations, such as recognizing constant in shape or color, whereas neural networks struggle. To investigate how neural networks generalize abstract relations, we intro…
Relational ReasoningRelation NetworkVisual ReasoningFinding the Trigger: Causal Abductive Reasoning on Video Events
This paper introduces a new problem, Causal Abductive Reasoning on Video Events (CARVE), which involves identifying causal relationships between events in a video and generating hypotheses about causal chains that accoun…
counterfactualManagementRelation NetworkRepresentation LearningARN-LSTM: A Multi-Stream Fusion Model for Skeleton-based Action Recognition
This paper presents the ARN-LSTM architecture, a novel multi-stream action recognition model designed to address the challenge of simultaneously capturing spatial motion and temporal dynamics in action sequences. Traditi…
Action RecognitionActivity RecognitionGroup Activity RecognitionRelation Network+1MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants
LLM-based agents have been widely applied as personal assistants, capable of memorizing information from user messages and responding to personal queries. However, there still lacks an objective and automatic evaluation …
DiversityRelation NetworkPersonalized federated learning based on feature fusion
Federated learning enables distributed clients to collaborate on training while storing their data locally to protect client privacy. However, due to the heterogeneity of data, models, and devices, the final global model…
Federated LearningPersonalized Federated LearningRelation NetworkAn All-MLP Sequence Modeling Architecture That Excels at Copying
Recent work demonstrated Transformers' ability to efficiently copy strings of exponential sizes, distinguishing them from other architectures. We present the Causal Relation Network (CausalRN), an all-MLP sequence modeli…
AllRelationRelation NetworkRetrievalLogical Reasoning with Relation Network for Inductive Knowledge Graph Completion
Inductive knowledge graph completion (KGC) aims to infer the missing relation for a set of newly-coming entities that never appeared in the training set. Such a setting is more in line with reality, as real-world KGs are…
Inductive knowledge graph completionKnowledge Graph CompletionLogical ReasoningRelation+1DHRNet: A Dual-Path Hierarchical Relation Network for Multi-Person Pose Estimation
Multi-person pose estimation (MPPE) presents a formidable yet crucial challenge in computer vision. Most existing methods predominantly concentrate on isolated interaction either between instances or joints, which is ina…
Multi-Person Pose EstimationPose EstimationRelationRelation NetworkDTCM: Deep Transformer Capsule Mutual Distillation for Multivariate Time Series Classification
This article proposes a dual-network-based feature extractor, perceptive capsule network (PCapN), for multivariate time series classification (MTSC), including a local feature network (LFN) and a global relation network …
Knowledge DistillationRelation NetworkTime SeriesTime Series Classification+1Visual Commonsense based Heterogeneous Graph Contrastive Learning
How to select relevant key objects and reason about the complex relationships cross vision and linguistic domain are two key issues in many multi-modality applications such as visual question answering (VQA). In this wor…
Contrastive LearningQuestion AnsweringRelationRelation Network+3Cyclic Directed Probabilistic Graphical Model: A Proposal Based on Structured Outcomes
In the process of building (structural learning) a probabilistic graphical model from a set of observed data, the directional, cyclic dependencies between the random variables of the model are often found. Existing graph…
Relation NetworkUnsupervised Representation Learning to Aid Semi-Supervised Meta Learning
Few-shot learning or meta-learning leverages the data scarcity problem in machine learning. Traditionally, training data requires a multitude of samples and labeling for supervised learning. To address this issue, we pro…
Few-Shot LearningMeta-LearningRelation NetworkRepresentation Learning+1IDRNet: Intervention-Driven Relation Network for Semantic Segmentation
Co-occurrent visual patterns suggest that pixel relation modeling facilitates dense prediction tasks, which inspires the development of numerous context modeling paradigms, \emph{e.g.}, multi-scale-driven and similarity-…
RelationRelation NetworkSemantic SegmentationFarSeg++: Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery
Geospatial object segmentation, a fundamental Earth vision task, always suffers from scale variation, the larger intraclass variance of background, and foreground-background imbalance in high spatial resolution (HSR) rem…
Earth ObservationRelationRelation NetworkSegmentation+2Multistage Relation Network With Dual-Metric for Few-Shot Hyperspectral Image Classification
Recently, few-shot learning (FSL) has exhibited great potential in the hyperspectral image (HSI) classification due to its promising performance under a few training samples. Although existing FSL methods have achieved g…
ClassificationFew-Shot Image ClassificationFew-Shot LearningHyperspectral Image Classification+4Relational Context Learning for Human-Object Interaction Detection
Recent state-of-the-art methods for HOI detection typically build on transformer architectures with two decoder branches, one for human-object pair detection and the other for interaction classification. Such disentangle…
DecoderHuman-Object Interaction DetectionObjectRelational Reasoning+1Kinship Representation Learning with Face Componential Relation
Kinship recognition aims to determine whether the subjects in two facial images are kin or non-kin, which is an emerging and challenging problem. However, most previous methods focus on heuristic designs without consider…
RelationRelation NetworkRepresentation LearningCycleACR: Cycle Modeling of Actor-Context Relations for Video Action Detection
The relation modeling between actors and scene context advances video action detection where the correlation of multiple actors makes their action recognition challenging. Existing studies model each actor and scene rela…
Action DetectionAction RecognitionRelationRelation Network+1You Only Need One Thing One Click: Self-Training for Weakly Supervised 3D Scene Understanding
3D scene understanding, e.g., point cloud semantic and instance segmentation, often requires large-scale annotated training data, but clearly, point-wise labels are too tedious to prepare. While some recent methods propo…
3D Instance SegmentationInstance SegmentationPseudo LabelRelation Network+3