1 citations · 1 across the 4 of their papers we have counts for
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TEn-CATG:Text-Enriched Audio-Visual Video Parsing with Multi-Scale Category-Aware Temporal Graph
Yaru Chen, Faegheh Sardari, Peiliang Zhang +4
Audio-visual video parsing (AVVP) aims to detect event categories and their temporal boundaries in videos, typically under weak supervision. Existing methods mainly focus on (i) im…
Teacher-Guided Pseudo Supervision and Cross-Modal Alignment for Audio-Visual Video Parsing
Yaru Chen, Ruohao Guo, Liting Gao +4
Weakly-supervised audio-visual video parsing (AVVP) seeks to detect audible, visible, and audio-visual events without temporal annotations. Previous work has emphasized refining gl…
CM-PIE: Cross-modal perception for interactive-enhanced audio-visual video parsing
Yaru Chen, Ruohao Guo, Xubo Liu +4
Audio-visual video parsing is the task of categorizing a video at the segment level with weak labels, and predicting them as audible or visible events. Recent methods for this task…
SOTR: Segmenting Objects with Transformers
Ruohao Guo, Dantong Niu, Liao Qu +1
Most recent transformer-based models show impressive performance on vision tasks, even better than Convolution Neural Networks (CNN). In this work, we present a novel, flexible, an…
LeafMask: Towards Greater Accuracy on Leaf Segmentation
Ruohao Guo, Liao Qu, Dantong Niu +2
Leaf segmentation is the most direct and effective way for high-throughput plant phenotype data analysis and quantitative researches of complex traits. Currently, the primary goal…