AAAI 2025 accepted papers on Detection and segmentation
181 of the 3,486 papers accepted at AAAI 2025 (5.2%) are on Detection and segmentation, compared with 5.3% at AAAI 2024. They fall into 5 topics.
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Topics and papers
Open-set and few-shot detection · 77 papers
- C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection (43 citations)
- Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community (27 citations)
- Fields of The World: A Machine Learning Benchmark Dataset for Global Agricultural Field Boundary Segmentation (16 citations)
- SAFIRE: Segment Any Forged Image Region (15 citations)
- Object-level Geometric Structure Preserving for Natural Image Stitching (14 citations)
- OV-DQUO: Open-Vocabulary DETR with Denoising Text Query Training and Open-World Unknown Objects Supervision (14 citations)
- FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring (13 citations)
- PhysAug: A Physical-guided and Frequency-based Data Augmentation for Single-Domain Generalized Object Detection (13 citations)
- CP-DETR: Concept Prompt Guide DETR Toward Stronger Universal Object Detection (11 citations)
- Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation (11 citations)
- Self-Prompting Analogical Reasoning for UAV Object Detection (11 citations)
- 3CAD: A Large-Scale Real-World 3C Product Dataset for Unsupervised Anomaly Detection (10 citations)
and 65 more in the interactive map.
CNN features · 59 papers
- Pinwheel-shaped Convolution and Scale-based Dynamic Loss for Infrared Small Target Detection (199 citations)
- Mamba YOLO: A Simple Baseline for Object Detection with State Space Model (169 citations)
- FBRT-YOLO: Faster and Better for Real-Time Aerial Image Detection (157 citations)
- HS-FPN: High Frequency and Spatial Perception FPN for Tiny Object Detection (108 citations)
- ConDSeg: A General Medical Image Segmentation Framework via Contrast-Driven Feature Enhancement (78 citations)
- RemDet: Rethinking Efficient Model Design for UAV Object Detection (44 citations)
- FD2-Net: Frequency-Driven Feature Decomposition Network for Infrared-Visible Object Detection (43 citations)
- Mesoscopic Insights: Orchestrating Multi-Scale & Hybrid Architecture for Image Manipulation Localization (32 citations)
- Ultra-High Resolution Segmentation via Boundary-Enhanced Patch-Merging Transformer (21 citations)
- SalM²: An Extremely Lightweight Saliency Mamba Model for Real-Time Cognitive Awareness of Driver Attention (19 citations)
- IRMamba: Pixel Difference Mamba with Layer Restoration for Infrared Small Target Detection (17 citations)
- S³-Mamba: Small-Size-Sensitive Mamba for Lesion Segmentation (15 citations)
and 47 more in the interactive map.
3D detection and driving · 21 papers
- Language Prompt for Autonomous Driving (62 citations)
- L4DR: LiDAR-4DRadar Fusion for Weather-Robust 3D Object Detection (27 citations)
- HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection (24 citations)
- GeoBEV: Learning Geometric BEV Representation for Multi-view 3D Object Detection (20 citations)
- UniDet3D: Multi-dataset Indoor 3D Object Detection (19 citations)
- RCTrans: Radar-Camera Transformer via Radar Densifier and Sequential Decoder for 3D Object Detection (15 citations)
- SCKD: Semi-Supervised Cross-Modality Knowledge Distillation for 4D Radar Object Detection (15 citations)
- Look Inside for More: Internal Spatial Modality Perception for 3D Anomaly Detection (12 citations)
- M3Net: Multimodal Multi-task Learning for 3D Detection, Segmentation, and Occupancy Prediction in Autonomous Driving (9 citations)
- PC-BEV: An Efficient Polar-Cartesian BEV Fusion Framework for LiDAR Semantic Segmentation (8 citations)
- DSRC: Learning Density-Insensitive and Semantic-Aware Collaborative Representation Against Corruptions (7 citations)
- MapExpert: Online HD Map Construction with Simple and Efficient Sparse Map Element Expert (5 citations)
and 9 more in the interactive map.
Tracking · 14 papers
- SUTrack: Towards Simple and Unified Single Object Tracking (50 citations)
- Exploring Enhanced Contextual Information for Video-Level Object Tracking (39 citations)
- Exploiting Multimodal Spatial-temporal Patterns for Video Object Tracking (29 citations)
- MambaLCT: Boosting Tracking via Long-term Context State Space Model (25 citations)
- Two-stream Beats One-stream: Asymmetric Siamese Network for Efficient Visual Tracking (25 citations)
- Less Is More: Token Context-Aware Learning for Object Tracking (22 citations)
- MM-Tracker: Motion Mamba for UAV-platform Multiple Object Tracking (15 citations)
- Temporal Coherent Object Flow for Multi-Object Tracking (11 citations)
- Patch-level Sounding Object Tracking for Audio-Visual Question Answering (10 citations)
- TGFormer: Transformer with Track Query Group for Multi-Object Tracking (6 citations)
- Cross-View Referring Multi-Object Tracking (5 citations)
- Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry (5 citations)
and 2 more in the interactive map.
Weakly supervised detection and segmentation · 10 papers
- MoRe: Class Patch Attention Needs Regularization for Weakly Supervised Semantic Segmentation (12 citations)
- MonoBox: Tightness-Free Box-Supervised Polyp Segmentation Using Monotonicity Constraint (9 citations)
- SGTC: Semantic-Guided Triplet Co-training for Sparsely Annotated Semi-Supervised Medical Image Segmentation (8 citations)
- Multi-clue Consistency Learning to Bridge Gaps Between General and Oriented Object in Semi-supervised Detection (7 citations)
- ScaleMatch: Multi-scale Consistency Enhancement for Semi-supervised Semantic Segmentation (7 citations)
- Weakly Supervised Gland Segmentation with Class Semantic Consistency and Purified Labels Filtration (7 citations)
- M²RL-Net: Multi-View and Multi-Level Relation Learning Network for Weakly-Supervised Image Forgery Detection (4 citations)
- Iterative Self-Training with Class-Aware Text-to-Image Synthesis for Visual Task Learning (2 citations)
- As Pseudo-Label Free as Possible: Leveraging Adaptive Feature Generation for Sparsely Annotated Object Detection
- BGHR: Bridging the Gap Between HBox-Supervised and RBox-Supervised Oriented Object Detection via Adaptive Fine-Grained Sample Mining
