95 citations · 217 across the 17 of their papers we have counts for
17 papers
Towards Complex-query Referring Image Segmentation: A Novel Benchmark
Wei Ji, Li Li, Hao Fei +4
Referring Image Understanding (RIS) has been extensively studied over the past decade, leading to the development of advanced algorithms. However, there has been a lack of research…
NExT-GPT: Any-to-Any Multimodal LLM
Shengqiong Wu, Hao Fei, Leigang Qu +2
While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides, they mostly fall prey to the limitation of only input-side multimodal understanding, without t…
In Defense of Clip-based Video Relation Detection
Meng Wei, Long Chen, Wei Ji +2
Video Visual Relation Detection (VidVRD) aims to detect visual relationship triplets in videos using spatial bounding boxes and temporal boundaries. Existing VidVRD methods can be…
Panoptic Scene Graph Generation with Semantics-Prototype Learning
Li Li, Wei Ji, Yiming Wu +4
Panoptic Scene Graph Generation (PSG) parses objects and predicts their relationships (predicate) to connect human language and visual scenes. However, different language preferenc…
Visually-Prompted Language Model for Fine-Grained Scene Graph Generation in an Open World
Qifan Yu, Juncheng Li, Yu Wu +3
Scene Graph Generation (SGG) aims to extract <subject, predicate, object> relationships in images for vision understanding. Although recent works have made steady progress on SGG,…
Multi-queue Momentum Contrast for Microvideo-Product Retrieval
Yali Du, Yinwei Wei, Wei Ji +3
The booming development and huge market of micro-videos bring new e-commerce channels for merchants. Currently, more micro-video publishers prefer to embed relevant ads into their…
Driving Style Recognition at First Impression for Online Trajectory Prediction
Tu Xu, Kan Wu, Yongdong Zhu +1
This paper proposes a new driving style recognition approach that allows autonomous vehicles (AVs) to perform trajectory predictions for surrounding vehicles with minimal data. Tow…
MetaComp: Learning to Adapt for Online Depth Completion
Yang Chen, Shanshan Zhao, Wei Ji +2
Relying on deep supervised or self-supervised learning, previous methods for depth completion from paired single image and sparse depth data have achieved impressive performance in…
Promoting Saliency From Depth: Deep Unsupervised RGB-D Saliency Detection
Wei Ji, Jingjing Li, Qi Bi +3
Growing interests in RGB-D salient object detection (RGB-D SOD) have been witnessed in recent years, owing partly to the popularity of depth sensors and the rapid progress of deep…
Content-Variant Reference Image Quality Assessment via Knowledge Distillation
Guanghao Yin, Wei Wang, Zehuan Yuan +4
Generally, humans are more skilled at perceiving differences between high-quality (HQ) and low-quality (LQ) images than directly judging the quality of a single LQ image. This situ…
Rethinking the Two-Stage Framework for Grounded Situation Recognition
Meng Wei, Long Chen, Wei Ji +2
Grounded Situation Recognition (GSR), i.e., recognizing the salient activity (or verb) category in an image (e.g., buying) and detecting all corresponding semantic roles (e.g., age…
Video as Conditional Graph Hierarchy for Multi-Granular Question Answering
Junbin Xiao, Angela Yao, Zhiyuan Liu +3
Video question answering requires the models to understand and reason about both the complex video and language data to correctly derive the answers. Existing efforts have been foc…
Deconfounded Video Moment Retrieval with Causal Intervention
Xun Yang, Fuli Feng, Wei Ji +2
We tackle the task of video moment retrieval (VMR), which aims to localize a specific moment in a video according to a textual query. Existing methods primarily model the matching…
Deep Learning for Weakly-Supervised Object Detection and Object Localization: A Survey
Feifei Shao, Long Chen, Jian Shao +5
Weakly-Supervised Object Detection (WSOD) and Localization (WSOL), i.e., detecting multiple and single instances with bounding boxes in an image using image-level labels, are long-…
Conditional Hyper-Network for Blind Super-Resolution with Multiple Degradations
Guanghao Yin, Wei Wang, Zehuan Yuan +5
Although single-image super-resolution (SISR) methods have achieved great success on single degradation, they still suffer performance drop with multiple degrading effects in real…
Boundary Proposal Network for Two-Stage Natural Language Video Localization
Shaoning Xiao, Long Chen, Songyang Zhang +4
We aim to address the problem of Natural Language Video Localization (NLVL)-localizing the video segment corresponding to a natural language description in a long and untrimmed vid…
Context-Aware Deep Spatio-Temporal Network for Hand Pose Estimation from Depth Images
Yiming Wu, Wei Ji, Xi Li +3
As a fundamental and challenging problem in computer vision, hand pose estimation aims to estimate the hand joint locations from depth images. Typically, the problem is modeled as…