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Object Categorization
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Object categorization identifies which label, from a given set, best corresponds to an image region defined by an input image and bounding box.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Divide and Conquer: Improving Multi-Camera 3D Perception with 2D Semantic-Depth Priors and Input-Dependent Queries
Comparing Apples to Oranges: LLM-powered Multimodal Intention Prediction in an Object Categorization Task
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception
Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers
Vocabulary-informed Zero-shot and Open-set Learning
Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark
Enhancing Fine-Grained 3D Object Recognition using Hybrid Multi-Modal Vision Transformer-CNN Models
Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks
GRIT: General Robust Image Task Benchmark
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Webly Supervised Concept Expansion for General Purpose Vision Models
Category-orthogonal object features guide information processing in recurrent neural networks trained for object categorization
Learning Transferable Visual Models From Natural Language Supervision
Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces
IAUnet: Global Context-Aware Feature Learning for Person Re-Identification
Local-HDP: Interactive Open-Ended 3D Object Categorization in Real-Time Robotic Scenarios
Learning Physical Graph Representations from Visual Scenes
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition
Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs
Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning
Look Further to Recognize Better: Learning Shared Topics and Category-Specific Dictionaries for Open-Ended 3D Object Recognition
Visualizing Representational Dynamics with Multidimensional Scaling Alignment
Learning robust visual representations using data augmentation invariance
Improved object recognition using neural networks trained to mimic the brain's statistical properties
PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras
Humans can decipher adversarial images
Grassmannian Discriminant Maps (GDM) for Manifold Dimensionality Reduction with Application to Image Set Classification
Part-Aware Fine-grained Object Categorization using Weakly Supervised Part Detection Network
Best sources forward: domain generalization through source-specific nets
Sparse, Collaborative, or Nonnegative Representation: Which Helps Pattern Classification?
Data augmentation instead of explicit regularization
Recurrent Convolutional Fusion for RGB-D Object Recognition
Multiple Manifolds Metric Learning with Application to Image Set Classification
A Simple Riemannian Manifold Network for Image Set Classification
Visual Object Categorization Based on Hierarchical Shape Motifs Learned From Noisy Point Cloud Decompositions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.