Brain signal visualization has emerged as an active research area, servi...
Click-based interactive segmentation enables productive pixel-level
anno...
CLIP (Contrastive Language-Image Pretraining) is well-developed for
open...
Video Instance Segmentation(VIS) aims at segmenting and categorizing obj...
Online camera-to-ground calibration is to generate a non-rigid body
tran...
In this paper, we consider the problem of simultaneously detecting objec...
Non-maximum suppression (NMS) is widely used in object detection pipelin...
Although deep learning methods have achieved advanced video object
recog...
The repairing work of terracotta warriors in Emperor Qinshihuang Mausole...
Entity-aware image captioning aims to describe named entities and events...
Temporal action detection (TAD) aims to determine the semantic label and...
Instance segmentation can detect where the objects are in an image, but ...
Classical recommender system methods typically face the filter bubble pr...
Cross domain recommender system constitutes a powerful method to tackle ...
In this work we present SwiftNet for real-time semi-supervised video obj...
Can our video understanding systems perceive objects when a heavy occlus...
Alongside the prevalence of mobile videos, the general public leans towa...
Current developments in temporal event or action localization usually ta...
Since the label collecting is prohibitive and time-consuming, unsupervis...
Multi-modal representation learning by pretraining has become an increas...
In this paper, we present a seed-region-growing CNN(SRG-Net) for unsuper...
Knowledge distillation aims at obtaining a small but effective deep mode...
Multi-label zero-shot classification aims to predict multiple unseen cla...
Click-through rate (CTR) prediction is an essential task in industrial
a...
Pedestrian detection in a crowd is very challenging due to vastly differ...
Most semantic segmentation models treat semantic segmentation as a pixel...
An increasing number of well-trained deep networks have been released on...
In this paper, we study the multi-objective bandits (MOB) problem, where...