Search Results for author:
Found 5 papers, 3 papers with code
SG-BEV: Satellite-Guided BEV Fusion for Cross-View Semantic Segmentation
This paper aims at achieving fine-grained building attribute segmentation in a cross-view scenario, i. e., using satellite and street-view image pairs.
VIGC: Visual Instruction Generation and Correction
A practical solution to this problem would be to utilize the available multimodal large language models (MLLMs) to generate instruction data for vision-language tasks.
SEPT: Towards Scalable and Efficient Visual Pre-Training
To address these issues, we build a task-specific self-supervised pre-training framework from a data selection perspective based on a simple hypothesis that pre-training on the unlabeled samples with similar distribution to the target task can bring substantial performance gains.
Influence Selection for Active Learning
To obtain the Influence of the unlabeled sample in the active learning scenario, we design the Untrained Unlabeled sample Influence Calculation(UUIC) to estimate the unlabeled sample's expected gradient with which we calculate its Influence.
