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Found 9 papers, 5 papers with code
Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups
Each learning group consists of a teacher network, a student network and a novel filter module.
Unsupervised Learning of Accurate Siamese Tracking
As unlimited self-supervision signals can be obtained by tracking a video along a cycle in time, we investigate evolving a Siamese tracker by tracking videos forward-backward.
Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking
Exploiting a general-purpose neural architecture to replace hand-wired designs or inductive biases has recently drawn extensive interest.
BN-NAS: Neural Architecture Search with Batch Normalization
We present BN-NAS, neural architecture search with Batch Normalization (BN-NAS), to accelerate neural architecture search (NAS).
PSViT: Better Vision Transformer via Token Pooling and Attention Sharing
Then, a compact set of the possible combinations for different token pooling and attention sharing mechanisms are constructed.
GLiT: Neural Architecture Search for Global and Local Image Transformer
We introduce the first Neural Architecture Search (NAS) method to find a better transformer architecture for image recognition.
Ranked #498 on
Image Classification
on ImageNet
Real-Time Visual Object Tracking via Few-Shot Learning
Visual Object Tracking (VOT) can be seen as an extended task of Few-Shot Learning (FSL).
GradNet: Gradient-Guided Network for Visual Object Tracking
In this work, we propose a novel gradient-guided network to exploit the discriminative information in gradients and update the template in the siamese network through feed-forward and backward operations.
Ranked #3 on
Visual Object Tracking
on OTB-2015
(Precision metric)
Real-time 'Actor-Critic' Tracking
In this work, we propose a novel tracking algorithm with real-time performance based on the âActor-Criticâ framework.
