Jun Ouyang, Qingwei Shi, Xinxin Wang, Liang Wang. Pedestrian Trajectory Prediction Based on GAN and Attention Mechanism[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141016
- Laser & Optoelectronics Progress
- Vol. 57, Issue 14, 141016 (2020)
Fig. 1. Overall architecture of GI-GAN model
Fig. 2. Comparison of model training loss. (a) Generated loss; (b) discriminant loss; (c) position offset loss
Fig. 3. ADE results of models under different K values. (a) S-GAN predicting loss; (b) GI-GAN-NA predicting loss; (c) GI-GAN predicting loss
Fig. 4. Comparison of prediction trajectories of different models. (a)-(g) Correct graphs of GI-GAN model trajectory prediction; (h)(i) error graphs of GI-GAN model trajectory prediction
Fig. 5. Multiple reasonable trajectories of GI-GAN-NA model
Fig. 6. Multiple reasonable trajectories of GI-GAN model
Fig. 7. Multiple reasonably predicted trajectories of same scene. (a) Maintain the original speed and turn to the horizontal direction; (b) slow down and wait, then turn to horizontal direction; (c) direct turn to the left and accelerate
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Table 1. Comparison of ADE results of three models under different K values
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Table 2. Comparison of ADE and FDE results of different models
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