https://github.com/dvlab-research/uvtr
공식 코드Unifying Voxel-based Representation with Transformer for 3D Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Unifying Voxel-based Representation with Transformer for 3D Object Detection
MFFN: Multi-view Feature Fusion Network for Camouflaged Object Detection
Learning to Prompt for Open-Vocabulary Object Detection with Vision-Language Model
EnsembleMOT: A Step towards Ensemble Learning of Multiple Object Tracking
VCVW-3D: A Virtual Construction Vehicles and Workers Dataset with 3D Annotations
SAM3D: Zero-Shot 3D Object Detection via Segment Anything Model
HuBo-VLM: Unified Vision-Language Model designed for HUman roBOt interaction tasks
TC-PDM: Temporally Consistent Patch Diffusion Models for Infrared-to-Visible Video Translation
Weakly Supervised Test-Time Domain Adaptation for Object Detection
Weakly-Supervised Learning of Visual Relations in Multimodal Pretraining
ModaNet: A Large-Scale Street Fashion Dataset with Polygon Annotations
Self-supervised Learning of LiDAR 3D Point Clouds via 2D-3D Neural Calibration
Spatial-Temporal Graph Enhanced DETR Towards Multi-Frame 3D Object Detection
Unleash the Potential of Image Branch for Cross-modal 3D Object Detection
OpenNav: Efficient Open Vocabulary 3D Object Detection for Smart Wheelchair Navigation
Benchmarking Unsupervised Object Representations for Video Sequences
Analysis of Training Object Detection Models with Synthetic Data
Genetic Learning for Designing Sim-to-Real Data Augmentations
A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images
Cooperative Perception for 3D Object Detection in Driving Scenarios using Infrastructure Sensors
Rethinking Transformer-based Set Prediction for Object Detection
Bayesian Confidence Calibration for Epistemic Uncertainty Modelling
Image and AIS Data Fusion Technique for Maritime Computer Vision Applications
Revising deep learning methods in parking lot occupancy detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.