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Found 13 papers, 3 papers with code
GraphBEV: Towards Robust BEV Feature Alignment for Multi-Modal 3D Object Detection
Additionally, we propose a Global Align module to rectify the misalignment between LiDAR and camera BEV features.
Instruction-Guided Scene Text Recognition
Multi-modal models have shown appealing performance in visual tasks recently, as instruction-guided training has evoked the ability to understand fine-grained visual content.
Robustness-Aware 3D Object Detection in Autonomous Driving: A Review and Outlook
In the realm of modern autonomous driving, the perception system is indispensable for accurately assessing the state of the surrounding environment, thereby enabling informed prediction and planning.
RoboFusion: Towards Robust Multi-Modal 3D Object Detection via SAM
To align SAM or SAM-AD with multi-modal methods, we then introduce AD-FPN for upsampling the image features extracted by SAM.
VoxelNextFusion: A Simple, Unified and Effective Voxel Fusion Framework for Multi-Modal 3D Object Detection
In particular, we propose a voxel-based image pipeline that involves projecting point clouds onto images to obtain both pixel- and patch-level features.
VGA: Vision and Graph Fused Attention Network for Rumor Detection
Moreover, these methods usually only extract visual features in a basic manner, seldom consider tampering or textual information in images.
GraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detection
Through the projection calibration between the image and point cloud, we project the nearest neighbors of point cloud features onto the image features.
Context Perception Parallel Decoder for Scene Text Recognition
We first present an empirical study of AR decoding in STR, and discover that the AR decoder not only models linguistic context, but also provides guidance on visual context perception.
Ranked #1 on
Scene Text Recognition
on CUTE80
(using extra training data)
Unsupervised Cross-Domain Rumor Detection with Contrastive Learning and Cross-Attention
Moreover, we use a cross-attention mechanism on a pair of source data and target data with the same labels to learn domain-invariant representations.
Deep Embedded Clustering with Distribution Consistency Preservation for Attributed Networks
Under the assumption of consistency for data in different views, the cluster structure of network topology and that of node attributes should be consistent for an attributed network.
SVTR: Scene Text Recognition with a Single Visual Model
Dominant scene text recognition models commonly contain two building blocks, a visual model for feature extraction and a sequence model for text transcription.
Ranked #15 on
Scene Text Recognition
on ICDAR2013
A Generative Node-attribute Network Model for Detecting Generalized Structure
Exploring meaningful structural regularities embedded in networks is a key to understanding and analyzing the structure and function of a network.
Attention Boosted Sequential Inference Model
Attention mechanism has been proven effective on natural language processing.
Ranked #1 on
Natural Language Inference
on Quora Question Pairs
