Object Categorization
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Benchmarks
GRIT
Most implemented
Learning Transferable Visual Models From Natural Language Supervision
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
Cost-Effective Active Learning for Deep Image Classification
Unsupervised Domain Adaptation through Inter-modal Rotation for RGB-D Object Recognition
Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs
Papers
Vision CNNs trained to estimate spatial latents learned similar ventral-stream-aligned representations
Studies of the functional role of the primate ventral visual stream have traditionally focused on object categorization, often ignoring -- despite much prior evidence -- its role in estimating "spatial" latents such as o…
Object CategorizationDivide and Conquer: Improving Multi-Camera 3D Perception with 2D Semantic-Depth Priors and Input-Dependent Queries
3D perception tasks, such as 3D object detection and Bird's-Eye-View (BEV) segmentation using multi-camera images, have drawn significant attention recently. Despite the fact that accurately estimating both semantic and …
3D Object DetectionBEV SegmentationObjectObject Categorization+3Comparing Apples to Oranges: LLM-powered Multimodal Intention Prediction in an Object Categorization Task
Human intention-based systems enable robots to perceive and interpret user actions to interact with humans and adapt to their behavior proactively. Therefore, intention prediction is pivotal in creating a natural interac…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Object Categorizationspeech-recognition+2Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception
Deep neural networks (DNNs) are known to have a fundamental sensitivity to adversarial attacks, perturbations of the input that are imperceptible to humans yet powerful enough to change the visual decision of a model. Ad…
Adversarial AttackAdversarial RobustnessDiagnosticObject Categorization+2Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifiers
Disaggregated performance metrics across demographic groups are a hallmark of fairness assessments in computer vision. These metrics successfully incentivized performance improvements on person-centric tasks such as face…
Fairnessimage-classificationImage ClassificationMulti-Label Image Classification+1Vocabulary-informed Zero-shot and Open-set Learning
Despite significant progress in object categorization, in recent years, a number of important challenges remain; mainly, the ability to learn from limited labeled data and to recognize object classes within large, potent…
Object CategorizationOpen Set LearningZero-Shot Learning