https://github.com/Gabriel-Macias/robust_frcnn
A Robust Learning Approach to Domain Adaptive Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Autonomous vehicles is the task of making a vehicle that can guide itself without human conduction.
Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.
<span style="color:grey; opacity: 0.6">( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
A Robust Learning Approach to Domain Adaptive Object Detection
Exploit the Connectivity: Multi-Object Tracking with TrackletNet
Attribution Preservation in Network Compression for Reliable Network Interpretation
Non-linear State-space Model Identification from Video Data using Deep Encoders
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices
HDMapNet: An Online HD Map Construction and Evaluation Framework
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.