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Found 6 papers, 4 papers with code
Multi-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning
Our model effectively handles the multi-modality of human motion and the complexity of long-term multi-agent interactions, improving performance in complex environments.
T4P: Test-Time Training of Trajectory Prediction via Masked Autoencoder and Actor-specific Token Memory
Our method surpasses the performance of existing state-of-the-art online learning methods in terms of both prediction accuracy and computational efficiency.
Improving Transferability for Cross-domain Trajectory Prediction via Neural Stochastic Differential Equation
To address this limitation, we propose a method based on continuous and stochastic representations of Neural Stochastic Differential Equations (NSDE) for alleviating discrepancies due to data acquisition strategy.
Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction
We also model the interaction using a probabilistic distribution, which allows for multiple possible future interactions.
Ranked #2 on
Trajectory Prediction
on nuScenes
BIPS: Bi-modal Indoor Panorama Synthesis via Residual Depth-aided Adversarial Learning
Providing omnidirectional depth along with RGB information is important for numerous applications, eg, VR/AR.
Unlocking the Potential of Ordinary Classifier: Class-Specific Adversarial Erasing Framework for Weakly Supervised Semantic Segmentation
In this paper, we review the potential of the pre-trained classifier which is trained on the raw images.
Ranked #30 on
Weakly-Supervised Semantic Segmentation
on COCO 2014 val
Weakly supervised Semantic Segmentation
Weakly-Supervised Semantic Segmentation
