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Found 8 papers, 4 papers with code
LoopAnimate: Loopable Salient Object Animation
The proposed LoopAnimate, which for the first time extends the single-pass generation length of UNet-based video generation models to 35 frames while maintaining high-quality video generation.
ADMap: Anti-disturbance framework for reconstructing online vectorized HD map
Therefore, this paper proposes the Anti-disturbance Map reconstruction framework (ADMap).
A Machine Vision Method for Correction of Eccentric Error: Based on Adaptive Enhancement Algorithm
Focusing on the severe defocus blur of reference crosshair image caused by the imaging characteristic of the aspherical optical element, which may lead to the failure of correction, an Adaptive Enhancement Algorithm (AEA) is proposed to strengthen the crosshair image.
GujiBERT and GujiGPT: Construction of Intelligent Information Processing Foundation Language Models for Ancient Texts
In the context of the rapid development of large language models, we have meticulously trained and introduced the GujiBERT and GujiGPT language models, which are foundational models specifically designed for intelligent information processing of ancient texts.
EA-LSS: Edge-aware Lift-splat-shot Framework for 3D BEV Object Detection
In recent years, great progress has been made in the Lift-Splat-Shot-based (LSS-based) 3D object detection method.
Ranked #1 on
3D Object Detection
on nuScenes
GAM : Gradient Attention Module of Optimization for Point Clouds Analysis
In point cloud analysis tasks, the existing local feature aggregation descriptors (LFAD) are unable to fully utilize information in the neighborhood of central points.
VA-GCN: A Vector Attention Graph Convolution Network for learning on Point Clouds
Owing to the development of research on local aggregation operators, dramatic breakthrough has been made in point cloud analysis models.
BAM: A Balanced Attention Mechanism for Single Image Super Resolution
The results demonstrate that BAM can efficiently improve the networks performance, and for those originally with attention mechanism, the substitution with BAM further reduces the amount of parameters and increases the inference speed.
