228 citations · 459 across the 33 of their papers we have counts for
22 papers · 1 filter
PanopticQuery: Unified Query-Time Reasoning for 4D Scenes
Ruilin Tang, Yang Zhou, Zhong Ye +3
Understanding dynamic 4D environments through natural language queries requires not only accurate scene reconstruction but also robust semantic grounding across space, time, and vi…
Adapting SAM to Nuclei Instance Segmentation and Classification via Cooperative Fine-Grained Refinement
Jingze Su, Tianle Zhu, Jiaxin Cai +6
Nuclei instance segmentation is critical in computational pathology for cancer diagnosis and prognosis. Recently, the Segment Anything Model has demonstrated exceptional performanc…
Stable Score Distillation
Haiming Zhu, Yangyang Xu, Chenshu Xu +5
Text-guided image and 3D editing have advanced with diffusion-based models, yet methods like Delta Denoising Score often struggle with stability, spatial control, and editing stren…
URWKV: Unified RWKV Model with Multi-state Perspective for Low-light Image Restoration
Rui Xu, Yuzhen Niu, Yuezhou Li +3
Existing low-light image enhancement (LLIE) and joint LLIE and deblurring (LLIE-deblur) models have made strides in addressing predefined degradations, yet they are often constrain…
Revisiting Network Perturbation for Semi-Supervised Semantic Segmentation
Sien Li, Tao Wang, Ruizhe Hu +1
In semi-supervised semantic segmentation (SSS), weak-to-strong consistency regularization techniques are widely utilized in recent works, typically combined with input-level and fe…
Distractor-aware Event-based Tracking
Yingkai Fu, Meng Li, Wenxi Liu +5
Event cameras, or dynamic vision sensors, have recently achieved success from fundamental vision tasks to high-level vision researches. Due to its ability to asynchronously capture…
Memory-Constrained Semantic Segmentation for Ultra-High Resolution UAV Imagery
Qi Li, Jiaxin Cai, Yuanlong Yu +3
Amidst the swift advancements in photography and sensor technologies, high-definition cameras have become commonplace in the deployment of Unmanned Aerial Vehicles (UAVs) for diver…
Frame-Event Alignment and Fusion Network for High Frame Rate Tracking
Jiqing Zhang, Yuanchen Wang, Wenxi Liu +4
Most existing RGB-based trackers target low frame rate benchmarks of around 30 frames per second. This setting restricts the tracker's functionality in the real world, especially f…
Single-View View Synthesis with Self-Rectified Pseudo-Stereo
Yang Zhou, Hanjie Wu, Wenxi Liu +3
Synthesizing novel views from a single view image is a highly ill-posed problem. We discover an effective solution to reduce the learning ambiguity by expanding the single-view vie…
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection
Wenxi Liu, Qi Li, Weixiang Yang +5
HD map reconstruction is crucial for autonomous driving. LiDAR-based methods are limited due to expensive sensors and time-consuming computation. Camera-based methods usually need…
Glance to Count: Learning to Rank with Anchors for Weakly-supervised Crowd Counting
Zheng Xiong, Liangyu Chai, Wenxi Liu +3
Crowd image is arguably one of the most laborious data to annotate. In this paper, we devote to reduce the massive demand of densely labeled crowd data, and propose a novel weakly-…
End-to-End Trajectory Distribution Prediction Based on Occupancy Grid Maps
Ke Guo, Wenxi Liu, Jia Pan
In this paper, we aim to forecast a future trajectory distribution of a moving agent in the real world, given the social scene images and historical trajectories. Yet, it is a chal…
Semi-Supervised Domain Generalization with Evolving Intermediate Domain
Luojun Lin, Han Xie, Zhishu Sun +4
Domain Generalization (DG) aims to generalize a model trained on multiple source domains to an unseen target domain. The source domains always require precise annotations, which ca…
Ultra-high Resolution Image Segmentation via Locality-aware Context Fusion and Alternating Local Enhancement
Wenxi Liu, Qi Li, Xindai Lin +3
Ultra-high resolution image segmentation has raised increasing interests in recent years due to its realistic applications. In this paper, we innovate the widely used high-resoluti…
Recurrent Distillation based Crowd Counting
Yue Gu, Wenxi Liu
In recent years, with the progress of deep learning technologies, crowd counting has been rapidly developed. In this work, we propose a simple yet effective crowd counting framewor…
Over-crowdedness Alert! Forecasting the Future Crowd Distribution
Yuzhen Niu, Weifeng Shi, Wenxi Liu +3
In recent years, vision-based crowd analysis has been studied extensively due to its practical applications in real world. In this paper, we formulate a novel crowd analysis proble…
Visualizing the Invisible: Occluded Vehicle Segmentation and Recovery
Xiaosheng Yan, Yuanlong Yu, Feigege Wang +3
In this paper, we propose a novel iterative multi-task framework to complete the segmentation mask of an occluded vehicle and recover the appearance of its invisible parts. In part…
Enhancement Mask for Hippocampus Detection and Segmentation
Dengsheng Chen, Wenxi Liu, You Huang +2
Detection and segmentation of the hippocampal structures in volumetric brain images is a challenging problem in the area of medical imaging. In this paper, we propose a two-stage 3…
Deformable Object Tracking with Gated Fusion
Wenxi Liu, Yibing Song, Dengsheng Chen +5
The tracking-by-detection framework receives growing attentions through the integration with the Convolutional Neural Networks (CNNs). Existing tracking-by-detection based methods,…
An Intelligent Extraversion Analysis Scheme from Crowd Trajectories for Surveillance
Wenxi Liu, Yuanlong Yu, Chun-Yang Zhang +2
In recent years, crowd analysis is important for applications such as smart cities, intelligent transportation system, customer behavior prediction, and visual surveillance. Unders…
Exemplar-AMMs: Recognizing Crowd Movements from Pedestrian Trajectories
Wenxi Liu, Rynson W. H. Lau, Xiaogang Wang +1
In this paper, we present a novel method to recognize the types of crowd movement from crowd trajectories using agent-based motion models (AMMs). Our idea is to apply a number of A…
Leveraging Long-Term Predictions and Online-Learning in Agent-based Multiple Person Tracking
Wenxi Liu, Antoni B. Chan, Rynson W. H. Lau +1
We present a multiple-person tracking algorithm, based on combining particle filters and RVO, an agent-based crowd model that infers collision-free velocities so as to predict pede…