Search Results for author:
Found 12 papers, 9 papers with code
Ray Denoising: Depth-aware Hard Negative Sampling for Multi-view 3D Object Detection
Multi-view 3D object detection systems often struggle with generating precise predictions due to the challenges in estimating depth from images, increasing redundant and incorrect detections.
Ranked #2 on
3D Object Detection
on nuScenes Camera Only
Multi-Centroid Representation Network for Domain Adaptive Person Re-ID
First, we present a Domain-Specific Contrastive Learning (DSCL) mechanism to fully explore intradomain information by comparing samples only from the same domain.
Contrastive Learning
Domain Adaptive Person Re-Identification
+2
EPNet++: Cascade Bi-directional Fusion for Multi-Modal 3D Object Detection
Recently, fusing the LiDAR point cloud and camera image to improve the performance and robustness of 3D object detection has received more and more attention, as these two modalities naturally possess strong complementarity.
Spatial Ensemble: a Novel Model Smoothing Mechanism for Student-Teacher Framework
Model smoothing is of central importance for obtaining a reliable teacher model in the student-teacher framework, where the teacher generates surrogate supervision signals to train the student.
Progressive and Aligned Pose Attention Transfer for Person Image Generation
This paper proposes a new generative adversarial network for pose transfer, i. e., transferring the pose of a given person to a target pose.
EPNet: Enhancing Point Features with Image Semantics for 3D Object Detection
In this paper, we aim at addressing two critical issues in the 3D detection task, including the exploitation of multiple sensors~(namely LiDAR point cloud and camera image), as well as the inconsistency between the localization and classification confidence.
TANet: Robust 3D Object Detection from Point Clouds with Triple Attention
In this paper, we focus on exploring the robustness of the 3D object detection in point clouds, which has been rarely discussed in existing approaches.
Asymmetric Non-local Neural Networks for Semantic Segmentation
The non-local module works as a particularly useful technique for semantic segmentation while criticized for its prohibitive computation and GPU memory occupation.
Ranked #15 on
Semantic Segmentation
on COCO-Stuff test
View N-gram Network for 3D Object Retrieval
By doing so, spatial information across multiple views is captured, which helps to learn a discriminative global embedding for each 3D object.
Progressive Pose Attention Transfer for Person Image Generation
This paper proposes a new generative adversarial network for pose transfer, i. e., transferring the pose of a given person to a target pose.
Ranked #1 on
Pose Transfer
on Market-1501
Deep-Person: Learning Discriminative Deep Features for Person Re-Identification
Recently, many methods of person re-identification (Re-ID) rely on part-based feature representation to learn a discriminative pedestrian descriptor.
Auto-Encoder Guided GAN for Chinese Calligraphy Synthesis
In this paper, we investigate the Chinese calligraphy synthesis problem: synthesizing Chinese calligraphy images with specified style from standard font(eg.
