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Found 14 papers, 3 papers with code
BEM: Balanced and Entropy-based Mix for Long-Tailed Semi-Supervised Learning
To this end, this paper introduces the Balanced and Entropy-based Mix (BEM), a pioneering mixing approach to re-balance the class distribution of both data quantity and uncertainty.
Text2Street: Controllable Text-to-image Generation for Street Views
Text-to-image generation has made remarkable progress with the emergence of diffusion models.
3rd Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation
In our solution, we regard the video panoptic segmentation task as a segmentation target querying task, represent both semantic and instance targets as a set of queries, and then combine these queries with video features extracted by neural networks to predict segmentation masks.
Perceive, Excavate and Purify: A Novel Object Mining Framework for Instance Segmentation
Then, we propose an object excavating mechanism to discover indistinguishable objects.
Motion-state Alignment for Video Semantic Segmentation
In recent years, video semantic segmentation has made great progress with advanced deep neural networks.
5th Place Solution for YouTube-VOS Challenge 2022: Video Object Segmentation
Video object segmentation (VOS) has made significant progress with the rise of deep learning.
InsCon:Instance Consistency Feature Representation via Self-Supervised Learning
On the other hand, InsCon introduces the pull and push of cell-instance, which utilizes cell consistency to enhance fine-grained feature representation for precise boundary localization.
Exploring Driving-aware Salient Object Detection via Knowledge Transfer
In this network, we construct an attentionbased knowledge transfer module to make up the knowledge difference.
Structure Guided Lane Detection
Next, multi-level structural constraints are used to improve the perception of lanes.
Ranked #29 on
Lane Detection
on CULane
Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss
Through these two attentions, we use the Purificatory Mechanism to impose strict weights with different regions of the whole salient objects and purify results from hard-to-distinguish regions, thus accurately predicting the locations and details of salient objects.
Exploring Reciprocal Attention for Salient Object Detection by Cooperative Learning
Typically, objects with the same semantics are not always prominent in images containing different backgrounds.
Distortion-adaptive Salient Object Detection in 360$^\circ$ Omnidirectional Images
Moreover, benchmarking results of the proposed baseline approach and other methods on 360$^\circ$ SOD dataset show the proposed dataset is very challenging, which also validate the usefulness of the proposed dataset and approach to boost the development of SOD on 360$^\circ$ omnidirectional scenes.
Selectivity or Invariance: Boundary-aware Salient Object Detection
In this network, the feature selectivity at boundaries is enhanced by incorporating a boundary localization stream, while the feature invariance at interiors is guaranteed with a complex interior perception stream.
Learning a Saliency Evaluation Metric Using Crowdsourced Perceptual Judgments
Due to the effectiveness of the learned metric, it also can be used to facilitate the development of new models for fixation prediction.
