Papers with Code 아카이브
Gait Recognition in the Wild
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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Gait Recognition in the Wild refers to methods under real-world senses, i.e., unconstrained environment.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
MimicGait: A Model Agnostic approach for Occluded Gait Recognition using Correlational Knowledge Distillation
It Takes Two: Accurate Gait Recognition in the Wild via Cross-granularity Alignment
GLGait: A Global-Local Temporal Receptive Field Network for Gait Recognition in the Wild
Parsing is All You Need for Accurate Gait Recognition in the Wild
Hierarchical Spatio-Temporal Representation Learning for Gait Recognition
Gait Recognition in Large-scale Free Environment via Single LiDAR
LidarGait: Benchmarking 3D Gait Recognition with Point Clouds
Gait Recognition in the Wild with Multi-hop Temporal Switch
Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline
Gait Recognition in the Wild with Dense 3D Representations and A Benchmark
VersatileGait: A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.