Search Results for author:
Found 11 papers, 3 papers with code
MixReorg: Cross-Modal Mixed Patch Reorganization is a Good Mask Learner for Open-World Semantic Segmentation
To address this issue, we propose MixReorg, a novel and straightforward pre-training paradigm for semantic segmentation that enhances a model's ability to reorganize patches mixed across images, exploring both local visual relevance and global semantic coherence.
Surfer: Progressive Reasoning with World Models for Robotic Manipulation
To conduct a comprehensive and systematic evaluation of the robot manipulation model in terms of language understanding and physical execution, we also created a robotic manipulation benchmark with progressive reasoning tasks, called SeaWave.
CapDet: Unifying Dense Captioning and Open-World Detection Pretraining
Besides, our CapDet also achieves state-of-the-art performance on dense captioning tasks, e. g., 15. 44% mAP on VG V1. 2 and 13. 98% on the VG-COCO dataset.
ViewCo: Discovering Text-Supervised Segmentation Masks via Multi-View Semantic Consistency
Specifically, we first propose text-to-views consistency modeling to learn correspondence for multiple views of the same input image.
Beyond Fixation: Dynamic Window Visual Transformer
Recently, a surge of interest in visual transformers is to reduce the computational cost by limiting the calculation of self-attention to a local window.
Unsupervised Person Re-Identification: A Systematic Survey of Challenges and Solutions
Therefore, comprehensive surveys on this topic are essential to summarise challenges and solutions to foster future research.
Person Search Challenges and Solutions: A Survey
This paper surveyed the recent works on image-based and text-based person search from the perspective of challenges and solutions.
A Comprehensive Survey of Scene Graphs: Generation and Application
For example, given an image, we want to not only detect and recognize objects in the image, but also know the relationship between objects (visual relationship detection), and generate a text description (image captioning) based on the image content.
NAS-TC: Neural Architecture Search on Temporal Convolutions for Complex Action Recognition
Accordingly, because of the automated design of its network structure, Neural architecture search (NAS) has achieved great success in the image processing field and attracted substantial research attention in recent years.
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions
Neural Architecture Search (NAS) is just such a revolutionary algorithm, and the related research work is complicated and rich.
