Papers Class-Incremental Object Detection
“Class-Incremental Object Detection” 태그가 달린 논문 17편 · 필터 해제
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic
Real-world object detection systems, such as those in autonomous driving and surveillance, must continuously learn new object categories and simultaneously adapt to changing environmental conditions. Existing approaches,…
Autonomous DrivingAvgClass-Incremental Object DetectionExemplar-Free+5Hierarchical Neural Collapse Detection Transformer for Class Incremental Object Detection
Recently, object detection models have witnessed notable performance improvements, particularly with transformer-based models. However, new objects frequently appear in the real world, requiring detection models to conti…
Class-Incremental Object DetectionObjectobject-detectionObject DetectionRevisiting Generative Replay for Class Incremental Object Detection
Generative replay has gained significant attention in class-incremental learning; however, its application to Class Incremental Object Detection (CIOD) remains limited due to the challenges in generating complex imag…
class-incremental learningClass Incremental LearningClass-Incremental Object DetectionIncremental Learning+2Latent Distillation for Continual Object Detection at the Edge
While numerous methods achieving remarkable performance exist in the Object Detection literature, addressing data distribution shifts remains challenging. Continual Learning (CL) offers solutions to this issue, enabling …
Class-Incremental Object DetectionContinual Learningobject-detectionObject DetectionYOLOOC: YOLO-based Open-Class Incremental Object Detection with Novel Class Discovery
Because of its use in practice, open-world object detection (OWOD) has gotten a lot of attention recently. The challenge is how can a model detect novel classes and then incrementally learn them without forgetting previo…
Class-Incremental Object DetectionNovel Class Discoveryobject-detectionObject Detection+1Learning Task-Aware Language-Image Representation for Class-Incremental Object Detection
Class-incremental object detection (CIOD) is a real-world desired capability, requiring an object detector to continuously adapt to new tasks without forgetting learned ones, with the main challenge being catastrophic fo…
Class-Incremental Object Detectionobject-detectionObject DetectionVLM-PL: Advanced Pseudo Labeling Approach for Class Incremental Object Detection via Vision-Language Model
In the field of Class Incremental Object Detection (CIOD), creating models that can continuously learn like humans is a major challenge. Pseudo-labeling methods, although initially powerful, struggle with multi-scenario …
Class-Incremental Object DetectionIncremental LearningLanguage ModelingLanguage Modelling+2SDDGR: Stable Diffusion-based Deep Generative Replay for Class Incremental Object Detection
In the field of class incremental learning (CIL), generative replay has become increasingly prominent as a method to mitigate the catastrophic forgetting, alongside the continuous improvements in generative models. Howev…
class-incremental learningClass Incremental LearningClass-Incremental Object DetectionIncremental Learning+3Incremental Object Detection with CLIP
In contrast to the incremental classification task, the incremental detection task is characterized by the presence of data ambiguity, as an image may have differently labeled bounding boxes across multiple continuous le…
Class-Incremental Object DetectionIncremental LearningLanguage ModelingLanguage Modelling+3Few-shot Class-incremental Learning for Classification and Object Detection: A Survey
Few-shot Class-Incremental Learning (FSCIL) presents a unique challenge in Machine Learning (ML), as it necessitates the Incremental Learning (IL) of new classes from sparsely labeled training samples without forgetting …
class-incremental learningClass Incremental LearningClass-Incremental Object DetectionFew-Shot Class-Incremental Learning+5Class-Incremental Learning of Plant and Disease Detection: Growing Branches with Knowledge Distillation
This paper investigates the problem of class-incremental object detection for agricultural applications where a model needs to learn new plant species and diseases incrementally without forgetting the previously learned …
class-incremental learningClass Incremental LearningClass-Incremental Object DetectionIncremental Learning+3Continual Detection Transformer for Incremental Object Detection
Incremental object detection (IOD) aims to train an object detector in phases, each with annotations for new object categories. As other incremental settings, IOD is subject to catastrophic forgetting, which is often add…
Class-Incremental Object DetectionKnowledge DistillationObjectobject-detection+1DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection
Deep learning has achieved notable success in 3D object detection with the advent of large-scale point cloud datasets. However, severe performance degradation in the past trained classes, i.e., catastrophic forgetting, s…
3D Object Detectionclass-incremental learningClass Incremental LearningClass-Incremental Object Detection+5Continual Object Detection: A review of definitions, strategies, and challenges
The field of Continual Learning investigates the ability to learn consecutive tasks without losing performance on those previously learned. Its focus has been mainly on incremental classification tasks. We believe that r…
Autonomous VehiclesClass-Incremental Object DetectionContinual LearningObject+2Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation
Traditional object detectors are ill-equipped for incremental learning. However, fine-tuning directly on a well-trained detection model with only new data will lead to catastrophic forgetting. Knowledge distillation is a…
Class-Incremental Object DetectionIncremental LearningKnowledge Distillationobject-detection+1Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection
Deep networks have shown remarkable results in the task of object detection. However, their performance suffers critical drops when they are subsequently trained on novel classes without any sample from the base classes …
Class-Incremental Object DetectionIncremental LearningObjectobject-detection+1Towards Class-incremental Object Detection with Nearest Mean of Exemplars
Incremental learning is a form of online learning. Incremental learning can modify the parameters and structure of the deep learning model so that the model does not forget the old knowledge while learning new knowledge.…
Class-Incremental Object DetectionIncremental Learningobject-detectionObject Detection