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Found 10 papers, 3 papers with code
Adaptive Anchor Label Propagation for Transductive Few-Shot Learning
Our novel algorithm, Adaptive Anchor Label Propagation}, outperforms the standard label propagation algorithm by as much as 7% and 2% in the 1-shot and 5-shot settings respectively.
Multi-Modal Hybrid Learning and Sequential Training for RGB-T Saliency Detection
To address this, we first propose a Multi-Modal Hybrid loss (MMHL) that comprises supervised and self-supervised loss functions.
Towards Automated Polyp Segmentation Using Weakly- and Semi-Supervised Learning and Deformable Transformers
Also, our framework can be utilized to fine-tune models trained on natural image segmentation datasets drastically improving their performance for polyp segmentation and impressively demonstrating superior performance to fully supervised fine-tuning.
NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
The challenge is composed of two tracks with an emphasis on fidelity and complexity constraints: In Track 1, participants are asked to optimize objective fidelity scores while imposing a low-complexity constraint (i. e. solutions can not exceed a given number of operations).
Diversity-based Trajectory and Goal Selection with Hindsight Experience Replay
We evaluate DTGSH on five challenging robotic manipulation tasks in simulated robot environments, where we show that our method can learn more quickly and reach higher performance than other state-of-the-art approaches on all tasks.
PhD Learning: Learning With Pompeiu-Hausdorff Distances for Video-Based Vehicle Re-Identification
Vehicle re-identification (re-ID) is of great significance to urban operation, management, security and has gained more attention in recent years.
Dynamic Knowledge Distillation With Noise Elimination for RGB-D Salient Object Detection
RGB-D salient object detection (SOD) demonstrates its superiority on detecting in complex environments due to the additional depth information introduced in the data.
Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection
We further introduce a mask-guided refinement module(MGRM) to complement the high-level semantic features and reduce the irrelevant features from multi-scale fusion, leading to an overall refinement of detection.
Salient Object Detection Combining a Self-attention Module and a Feature Pyramid Network
Salient object detection has achieved great improvement by using the Fully Convolution Network (FCN).
Gated Multi-layer Convolutional Feature Extraction Network for Robust Pedestrian Detection
In this paper, we propose a gated multi-layer convolutional feature extraction method which can adaptively generate discriminative features for candidate pedestrian regions.
