Search Results for author:
Found 9 papers, 4 papers with code
PTT: Point-Trajectory Transformer for Efficient Temporal 3D Object Detection
Recent temporal LiDAR-based 3D object detectors achieve promising performance based on the two-stage proposal-based approach.
Weakly Supervised 3D Object Detection via Multi-Level Visual Guidance
Finally, the training-level constraint is utilized by producing accurate and consistent 3D pseudo-labels that align with the visual data.
Delving into Motion-Aware Matching for Monocular 3D Object Tracking
In this paper, we find that the motion cue of objects along different time frames is critical in 3D multi-object tracking, which is less explored in existing monocular-based approaches.
MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer
Moreover, different from conventional pixel-wise positional encodings, we introduce a novel depth positional encoding (DPE) to inject depth positional hints into transformers.
D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation
In the field of domain adaptation, a trade-off exists between the model performance and the number of target domain annotations.
3rd Place Solution for NeurIPS 2021 Shifts Challenge: Vehicle Motion Prediction
Shifts Challenge: Robustness and Uncertainty under Real-World Distributional Shift is a competition held by NeurIPS 2021.
Multi-Stream Attention Learning for Monocular Vehicle Velocity and Inter-Vehicle Distance Estimation
Vehicle velocity and inter-vehicle distance estimation are essential for ADAS (Advanced driver-assistance systems) and autonomous vehicles.
LAFFNet: A Lightweight Adaptive Feature Fusion Network for Underwater Image Enhancement
The model is the encoder-decoder model with multiple adaptive feature fusion (AAF) modules.
Adaptive Subspace Sampling for Class Imbalance Processing-Some clarifications, algorithm, and further investigation including applications to Brain Computer Interface
This investigation extends that study, clarifies some issues related to our earlier work, provides the algorithm for generation of the oversamples, applies the method on several benchmark data sets, and makes application to three Brain Computer Interface (BCI) applications.
