Research map / Detection and segmentation
Open-set and few-shot detection: research map
1,888 accepted papers on Open-set and few-shot detection in Detection and segmentation, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 6 clusters and 22 approaches. The busiest year so far is 2024.
Within Detection and segmentation, its share held steady from 46.8% in 2023–24 to 46.0% in 2025–26 (588 → 554 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).
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Approaches and key papers
images · anomaly · interactive · 878 papers
Approaches in this cluster:
- Object-level representation learning (219 papers)
Learn object-centric recognition features through contrastive pretraining and context debiasing. - Open-set and unknown object detection (160 papers)
Detect unknown objects by modeling latent regions, geometry cues, and class-agnostic prompts. - Interactive and referring segmentation (161 papers)
Segment objects from clicks or language expressions with refinement pipelines. - Amodal and open-world instance segmentation (137 papers)
Segment instances, including occluded ones, without annotations using pseudo labels. - Industrial anomaly detection (117 papers)
Detect anomalies with student-teacher, multi-sensor, and likelihood-based methods. - Remote sensing segmentation and change (84 papers)
Build datasets and models for geospatial segmentation and change detection.
Most cited and most cited since 2024:
- The Cityscapes Dataset for Semantic Urban Scene Understanding (CVPR 2016 · 12,279 citations)
- Scene Parsing Through ADE20K Dataset (CVPR 2017 · 3,305 citations)
- VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning (CVPR 2024 · 129 citations)
- Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection (CVPR 2024 · 127 citations)
human · interaction · hoi · 295 papers
Approaches in this cluster:
- Unsupervised object and part discovery (114 papers)
Discover objects and parts without labels through contrastive reconstruction and background cues. - Human-object interaction detection (66 papers)
Detect human-object interactions with cross-modal, pose-aware, and knowledge-guided models. - Visual relationship and scene graph detection (63 papers)
Detect object relations and generate scene graphs with context and reinforcement learning. - Hand-object and articulated interaction (52 papers)
Model and generate hand-object and articulated object manipulation.
Most cited and most cited since 2024:
- DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks (CVPR 2018 · 1,784 citations)
- Unsupervised Representation Learning by Predicting Image Rotations (ICLR 2018 · 1,506 citations)
- Improving Audio-Visual Segmentation with Bidirectional Generation (AAAI 2024 · 32 citations)
- Error Detection in Egocentric Procedural Task Videos (CVPR 2024 · 31 citations)
vocabulary · language · text · 230 papers
Approaches in this cluster:
- Open-vocabulary object detection (96 papers)
Detect novel categories by distilling vision-language knowledge into detectors. - Open-vocabulary semantic segmentation (93 papers)
Segment arbitrary categories using CLIP, mask adaptation, and diffusion without dense labels. - Open-vocabulary 3D and world perception (41 papers)
Extend open-vocabulary understanding to 3D instances, open-world detection, and language-guided segmentation.
Most cited and most cited since 2024:
- LVIS: A Dataset for Large Vocabulary Instance Segmentation (CVPR 2019 · 1,281 citations)
- VinVL: Revisiting Visual Representations in Vision-Language Models (CVPR 2021 · 894 citations)
- YOLO-World: Real-Time Open-Vocabulary Object Detection (CVPR 2024 · 721 citations)
- OMG-Seg: Is One Model Good Enough For All Segmentation? (CVPR 2024 · 77 citations)
zero · shot object · shot segmentation · 219 papers
Approaches in this cluster:
- Few-shot object detection (67 papers)
Detect novel classes from few examples with contrastive proposals and incremental learning. - Few-shot segmentation (64 papers)
Segment novel classes from few support images using pretrained features and aggregation. - Zero-shot segmentation and detection (49 papers)
Recognize unseen classes via generative features and semantic alignment. - Prompted SAM segmentation (39 papers)
Adapt Segment Anything for semantic, point-prompted, and efficient few-shot segmentation.
Most cited and most cited since 2024:
- Grounded Language-Image Pre-Training (CVPR 2022 · 1,055 citations)
- Synthesized Classifiers for Zero-Shot Learning (CVPR 2016 · 713 citations)
- EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything (CVPR 2024 · 240 citations)
- AnyDoor: Zero-shot Object-level Image Customization (CVPR 2024 · 175 citations)
domain · adaptation · adaptive object · 160 papers
Approaches in this cluster:
- Domain-adaptive object detection (103 papers)
Adapt detectors across domains with alignment, diversity, and mean-teacher methods. - Domain-adaptive segmentation (27 papers)
Transfer segmentation across domains using pixel-level association and foundation models. - Cross-domain translation and pose (30 papers)
Handle cross-domain tasks through relation-aware teachers, image translation, and decomposition.
Most cited and most cited since 2024:
- Domain Adaptive Faster R-CNN for Object Detection in the Wild (CVPR 2018 · 1,649 citations)
- Strong-Weak Distribution Alignment for Adaptive Object Detection (CVPR 2019 · 824 citations)
- Stronger Fewer & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation (CVPR 2024 · 101 citations)
- Boosting Object Detection with Zero-Shot Day-Night Domain Adaptation (CVPR 2024 · 71 citations)
object centric · slot · representations · 106 papers
Approaches in this cluster:
- Object-centric learning theory and video (86 papers)
Learn object-centric representations with identifiability, robustness analysis, and video conditioning. - Slot attention methods (20 papers)
Extend slot attention with grounding, invariance, and query optimization for object discovery.
Most cited and most cited since 2024:
- Object-Centric Auto-Encoders and Dummy Anomalies for Abnormal Event Detection in Video (CVPR 2019 · 432 citations)
- Object-Centric Learning with Slot Attention (NeurIPS 2020 · 211 citations)
- Prompt-Driven Dynamic Object-Centric Learning for Single Domain Generalization (CVPR 2024 · 26 citations)
- EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation (CVPR 2024 · 20 citations)
Related topics in Detection and segmentation
- Tracking (311)
- 3D detection and driving (458)
- CNN features (1,734)
- Weakly supervised detection and segmentation (436)