8 citations · 24 across the 13 of their papers we have counts for
14 papers
Improving Video Colorization by Test-Time Tuning
Yaping Zhao, Haitian Zheng, Jiebo Luo +1
With the advancements in deep learning, video colorization by propagating color information from a colorized reference frame to a monochrome video sequence has been well explored.…
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
Wenwen Yu, Chengquan Zhang, Haoyu Cao +24
Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, an…
Unveiling Cross Modality Bias in Visual Question Answering: A Causal View with Possible Worlds VQA
Ali Vosoughi, Shijian Deng, Songyang Zhang +3
To increase the generalization capability of VQA systems, many recent studies have tried to de-bias spurious language or vision associations that shortcut the question or image to…
3D Point Cloud Pre-training with Knowledge Distillation from 2D Images
Yuan Yao, Yuanhan Zhang, Zhenfei Yin +3
The recent success of pre-trained 2D vision models is mostly attributable to learning from large-scale datasets. However, compared with 2D image datasets, the current pre-training…
A Unified Framework for Contrastive Learning from a Perspective of Affinity Matrix
Wenbin Li, Meihao Kong, Xuesong Yang +4
In recent years, a variety of contrastive learning based unsupervised visual representation learning methods have been designed and achieved great success in many visual tasks. Gen…
Contextual Modeling for 3D Dense Captioning on Point Clouds
Yufeng Zhong, Long Xu, Jiebo Luo +1
3D dense captioning, as an emerging vision-language task, aims to identify and locate each object from a set of point clouds and generate a distinctive natural language sentence fo…
Point Cloud Denoising via Momentum Ascent in Gradient Fields
Yaping Zhao, Haitian Zheng, Zhongrui Wang +2
To achieve point cloud denoising, traditional methods heavily rely on geometric priors, and most learning-based approaches suffer from outliers and loss of details. Recently, the g…
MANet: Improving Video Denoising with a Multi-Alignment Network
Yaping Zhao, Haitian Zheng, Zhongrui Wang +2
In video denoising, the adjacent frames often provide very useful information, but accurate alignment is needed before such information can be harnassed. In this work, we present a…
SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Editing
Jing Shi, Ning Xu, Haitian Zheng +3
Recently, large pretrained models (e.g., BERT, StyleGAN, CLIP) have shown great knowledge transfer and generalization capability on various downstream tasks within their domains. I…
LUAI Challenge 2021 on Learning to Understand Aerial Images
Gui-Song Xia, Jian Ding, Ming Qian +33
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in a…
Multi-Modulation Network for Audio-Visual Event Localization
Hao Wang, Zheng-Jun Zha, Liang Li +2
We study the problem of localizing audio-visual events that are both audible and visible in a video. Existing works focus on encoding and aligning audio and visual features at the…
Trip-ROMA: Self-Supervised Learning with Triplets and Random Mappings
Wenbin Li, Xuesong Yang, Meihao Kong +4
Contrastive self-supervised learning (SSL) methods, such as MoCo and SimCLR, have achieved great success in unsupervised visual representation learning. They rely on a large number…
Memory Enhanced Embedding Learning for Cross-Modal Video-Text Retrieval
Rui Zhao, Kecheng Zheng, Zheng-Jun Zha +2
Cross-modal video-text retrieval, a challenging task in the field of vision and language, aims at retrieving corresponding instance giving sample from either modality. Existing app…
When Few-Shot Learning Meets Video Object Detection
Zhongjie Yu, Gaoang Wang, Lin Chen +2
Different from static images, videos contain additional temporal and spatial information for better object detection. However, it is costly to obtain a large number of videos with…