Search Results for author:
Found 7 papers, 4 papers with code
Layered Neighborhood Expansion for Incremental Multiple Graph Matching
In this paper, we treat the graphs as graphs on a super-graph, and propose a novel breadth first search based method for expanding the neighborhood on the super-graph for a new coming graph, such that the matching with the new graph can be efficiently performed within the constructed neighborhood.
DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention
In this paper, a detail-enhanced attention block (DEAB) consisting of the detail-enhanced convolution (DEConv) and the content-guided attention (CGA) is proposed to boost the feature learning for improving the dehazing performance.
Ranked #1 on
Image Dehazing
on Haze4k
Semantic Segmentation on VSPW Dataset through Aggregation of Transformer Models
Semantic segmentation is an important task in computer vision, from which some important usage scenarios are derived, such as autonomous driving, scene parsing, etc.
Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users
Online shopping has become a valuable modern convenience, but blind or low vision (BLV) users still face significant challenges using it, because of: 1) inadequate image descriptions and 2) the inability to filter large amounts of information using screen readers.
Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues
As realistic facial manipulation technologies have achieved remarkable progress, social concerns about potential malicious abuse of these technologies bring out an emerging research topic of face forgery detection.
You Impress Me: Dialogue Generation via Mutual Persona Perception
Despite the continuing efforts to improve the engagingness and consistency of chit-chat dialogue systems, the majority of current work simply focus on mimicking human-like responses, leaving understudied the aspects of modeling understanding between interlocutors.
Ranked #1 on
Dialogue Generation
on Persona-Chat
Contour Loss: Boundary-Aware Learning for Salient Object Segmentation
Yet the Contour Loss emphasizes on the local saliency.
