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Found 9 papers, 0 papers with code
MV-CLIP: Multi-View CLIP for Zero-shot 3D Shape Recognition
Consequently, this paper aims to improve the confidence with view selection and hierarchical prompts.
Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic Segmentation
Existing methods of cross-modal domain adaptation for 3D semantic segmentation predict results only via 2D-3D complementarity that is obtained by cross-modal feature matching.
Learning Memory-Augmented Unidirectional Metrics for Cross-Modality Person Re-Identification
These two unidirectional metrics (IR image to RGB proxy and RGB image to IR proxy) jointly alleviate the relay effect and benefit cross-modality association.
Cross-Modality Person Re-identification
Person Re-Identification
On Skew Convolutional and Trellis Codes
Two new classes of skew codes over a finite field $\F$ are proposed, called skew convolutional codes and skew trellis codes.
Information Theory Information Theory
Memory-based Jitter: Improving Visual Recognition on Long-tailed Data with Diversity In Memory
With slight modifications, MBJ is applicable for two fundamental visual recognition tasks, \emph{i. e.}, deep image classification and deep metric learning (on long-tailed data).
Ranked #44 on
Long-tail Learning
on CIFAR-100-LT (ρ=100)
Deep Representation Learning on Long-tailed Data: A Learnable Embedding Augmentation Perspective
If a sample belongs to a tail class, the corresponding feature cloud will have relatively large distribution range, in compensation to its lack of diversity.
Saliency guided deep network for weakly-supervised image segmentation
Classification activation mapping is a common method which can be used to generate high-precise object location cues.
Self-Attention Recurrent Network for Saliency Detection
Therefore, the network generates elaborate saliency maps by enhancing local and global information of feature maps in different layers.
Multi-Camera Action Dataset for Cross-Camera Action Recognition Benchmarking
To enable the study of this problem, there exist a vast number of action datasets, which are recorded under controlled laboratory settings, real-world surveillance environments, or crawled from the Internet.
