Object Recognition
486 papers with code • 7 benchmarks • 42 datasets
Object recognition is a computer vision technique for detecting + classifying objects in images or videos. Since this is a combined task of object detection plus image classification, the state-of-the-art tables are recorded for each component task here and here.
( Image credit: Tensorflow Object Detection API )
Benchmarks
These leaderboards are used to track progress in Object Recognition
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Libraries
Use these libraries to find Object Recognition models and implementationsDatasets
CIFAR-10
ImageNet
CORe50
N-Caltech 101
DVS128 Gesture
SUN Attribute
OCID
CIFAR10-DVS
Latest papers with no code
Object-conditioned Bag of Instances for Few-Shot Personalized Instance Recognition
Nowadays, users demand for increased personalization of vision systems to localize and identify personal instances of objects (e. g., my dog rather than dog) from a few-shot dataset only.
SUGAR: Pre-training 3D Visual Representations for Robotics
SUGAR employs a versatile transformer-based model to jointly address five pre-training tasks, namely cross-modal knowledge distillation for semantic learning, masked point modeling to understand geometry structures, grasping pose synthesis for object affordance, 3D instance segmentation and referring expression grounding to analyze cluttered scenes.
Efficient Multi-Band Temporal Video Filter for Reducing Human-Robot Interaction
Although mobile robots have on-board sensors to perform navigation, their efficiency in completing paths can be enhanced by planning to avoid human interaction.
PseudoTouch: Efficiently Imaging the Surface Feel of Objects for Robotic Manipulation
We frame this problem as the task of learning a low-dimensional visual-tactile embedding, wherein we encode a depth patch from which we decode the tactile signal.
EventDance: Unsupervised Source-free Cross-modal Adaptation for Event-based Object Recognition
To this end, we propose a novel framework, dubbed EventDance for this unsupervised source-free cross-modal adaptation problem.
Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures
Recent model inversion attack algorithms permit adversaries to reconstruct a neural network's private training data just by repeatedly querying the network and inspecting its outputs.
Towards Real-Time Fast Unmanned Aerial Vehicle Detection Using Dynamic Vision Sensors
Unmanned Aerial Vehicles (UAVs) are gaining popularity in civil and military applications.
ViTCN: Vision Transformer Contrastive Network For Reasoning
Machine learning models have achieved significant milestones in various domains, for example, computer vision models have an exceptional result in object recognition, and in natural language processing, where Large Language Models (LLM) like GPT can start a conversation with human-like proficiency.
Latent Object Characteristics Recognition with Visual to Haptic-Audio Cross-modal Transfer Learning
Recognising the characteristics of objects while a robot handles them is crucial for adjusting motions that ensure stable and efficient interactions with containers.
Generalized Relevance Learning Grassmann Quantization
The proposed model returns a set of prototype subspaces and a relevance vector.
