Search Results for author:
Found 13 papers, 1 papers with code
Cross-modal Contrastive Attention Model for Medical Report Generation
Medical report automatic generation has gained increasing interest recently as a way to help radiologists write reports more efficiently.
SparseLIF: High-Performance Sparse LiDAR-Camera Fusion for 3D Object Detection
Sparse 3D detectors have received significant attention since the query-based paradigm embraces low latency without explicit dense BEV feature construction.
Rethinking Radiology Report Generation via Causal Reasoning and Counterfactual Augmentation
Radiology Report Generation (RRG) draws attention as an interaction between vision and language fields.
Filter and evolve: progressive pseudo label refining for semi-supervised automatic speech recognition
The model is iteratively updated to correct the unreliable pseudo labels to minimize the effect of noisy labels.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
AdaStereo: An Efficient Domain-Adaptive Stereo Matching Approach
Compared to previous methods, our AdaStereo realizes a more standard, complete and effective domain adaptation pipeline.
LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation
However, two major issues of the fusion between camera and LiDAR hinder its performance, \ie, how to effectively fuse these two modalities and how to precisely align them (suffering from the weak spatiotemporal synchronization problem).
Temporal-Channel Transformer for 3D Lidar-Based Video Object Detection in Autonomous Driving
As a special design of this transformer, the information encoded in the encoder is different from that in the decoder, i. e. the encoder encodes temporal-channel information of multiple frames while the decoder decodes the spatial-channel information for the current frame in a voxel-wise manner.
Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation
A straightforward solution to tackle the issue of 3D-to-2D projection is to keep the 3D representation and process the points in the 3D space.
Ranked #11 on
LIDAR Semantic Segmentation
on nuScenes
AdaStereo: A Simple and Efficient Approach for Adaptive Stereo Matching
Compared to previous methods for adaptive stereo matching, our AdaStereo realizes a more standard, complete and effective domain adaptation pipeline.
EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection
EdgeStereo also achieves comparable generalization performance for disparity estimation because of the incorporation of edge cues.
Discriminative Representation Combinations for Accurate Face Spoofing Detection
Secondly we utilize the SSD, which is a deep learning framework for detection, to excavate context cues and conduct end-to-end face presentation attack detection.
EdgeStereo: A Context Integrated Residual Pyramid Network for Stereo Matching
Recent convolutional neural networks, especially end-to-end disparity estimation models, achieve remarkable performance on stereo matching task.
Face Spoofing Detection by Fusing Binocular Depth and Spatial Pyramid Coding Micro-Texture Features
The second one is a high-level micro-texture based feature called Spatial Pyramid Coding Micro-Texture (SPMT) feature.
