Publications (41)
A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation
Shuting He, Peilin Ji, Yitong Yang +4
In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radiance Field (NeRF), enabling high…
HRSeg: High-Resolution Visual Perception and Enhancement for Reasoning Segmentation
Weihuang Lin, Yiwei Ma, Xiaoshuai Sun +4
The reasoning segmentation task involves segmenting objects within an image by interpreting implicit user instructions, which may encompass subtleties such as contextual cues and o…
Semantic-Promoted Debiasing and Background Disambiguation for Zero-Shot Instance Segmentation
Shuting He, Henghui Ding, Wei Jiang
Zero-shot instance segmentation aims to detect and precisely segment objects of unseen categories without any training samples. Since the model is trained on seen categories, there…
ReferSplat: Referring Segmentation in 3D Gaussian Splatting
Shuting He, Guangquan Jie, Changshuo Wang +4
We introduce Referring 3D Gaussian Splatting Segmentation (R3DGS), a new task that aims to segment target objects in a 3D Gaussian scene based on natural language descriptions, whi…
SplitFlux: Learning to Decouple Content and Style from a Single Image
Yitong Yang, Yinglin Wang, Changshuo Wang +3
Disentangling image content and style is essential for customized image generation. Existing SDXL-based methods struggle to achieve high-quality results, while the recently propose…
WBCAtt+: Fine-Grained Pixel-Level Morphological Annotations for White Blood Cell Images
Satoshi Tsutsui, Winnie Pang, Shuting He +1
The microscopic examination of white blood cells (WBCs) plays a fundamental role in pathology and is essential for diagnosing blood disorders such as leukemia and anemia. To suppor…
Prompt-Softbox-Prompt: A Free-Text Embedding Control for Image Editing
Yitong Yang, Yinglin Wang, Tian Zhang +2
While text-driven diffusion models demonstrate remarkable performance in image editing, the critical components of their text embeddings remain underexplored. The ambiguity and ent…
Multimodal Referring Segmentation: A Survey
Henghui Ding, Song Tang, Shuting He +3
Multimodal referring segmentation aims to segment target objects in visual scenes, such as images, videos, and 3D scenes, based on referring expressions in text or audio format. Th…
MOSEv2: A More Challenging Dataset for Video Object Segmentation in Complex Scenes
Henghui Ding, Kaining Ying, Chang Liu +5
Video object segmentation (VOS) aims to segment specified target objects throughout a video. Although state-of-the-art methods have achieved impressive performance (e.g., 90+% J&F)…
GREx: Generalized Referring Expression Segmentation, Comprehension, and Generation
Henghui Ding, Chang Liu, Shuting He +2
Referring Expression Segmentation (RES) and Comprehension (REC) respectively segment and detect the object described by an expression, while Referring Expression Generation (REG) g…
ZoRI: Towards Discriminative Zero-Shot Remote Sensing Instance Segmentation
Shiqi Huang, Shuting He, Bihan Wen
Instance segmentation algorithms in remote sensing are typically based on conventional methods, limiting their application to seen scenarios and closed-set predictions. In this wor…
Region Generation and Assessment Network for Occluded Person Re-Identification
Shuting He, Weihua Chen, Kai Wang +4
Person Re-identification (ReID) plays a more and more crucial role in recent years with a wide range of applications. Existing ReID methods are suffering from the challenges of mis…
SegPoint: Segment Any Point Cloud via Large Language Model
Shuting He, Henghui Ding, Xudong Jiang +1
Despite significant progress in 3D point cloud segmentation, existing methods primarily address specific tasks and depend on explicit instructions to identify targets, lacking the…
Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding
Chang Liu, Henghui Ding, Nikhila Ravi +40
This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…
MeViS: A Multi-Modal Dataset for Referring Motion Expression Video Segmentation
Henghui Ding, Chang Liu, Shuting He +4
This paper proposes a large-scale multi-modal dataset for referring motion expression video segmentation, focusing on segmenting and tracking target objects in videos based on lang…
PVUW 2025 Challenge Report: Advances in Pixel-level Understanding of Complex Videos in the Wild
Henghui Ding, Chang Liu, Nikhila Ravi +33
This report provides a comprehensive overview of the 4th Pixel-level Video Understanding in the Wild (PVUW) Challenge, held in conjunction with CVPR 2025. It summarizes the challen…
Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models
Hao Wang, Licheng Pan, Yuan Lu +7
The design of training objective is central to training time-series forecasting models. Existing training objectives such as mean squared error mostly treat each future step as an…
Context-Aware Integration of Language and Visual References for Natural Language Tracking
Yanyan Shao, Shuting He, Qi Ye +3
Tracking by natural language specification (TNL) aims to consistently localize a target in a video sequence given a linguistic description in the initial frame. Existing methodolog…
RSGround-R1: Rethinking Remote Sensing Visual Grounding through Spatial Reasoning
Shiqi Huang, Shuting He, Bihan Wen
Remote Sensing Visual Grounding (RSVG) aims to localize target objects in large-scale aerial imagery based on natural language descriptions. Owing to the vast spatial scale and hig…
An Empirical Study of Vehicle Re-Identification on the AI City Challenge
Hao Luo, Weihua Chen, Xianzhe Xu +7
This paper introduces our solution for the Track2 in AI City Challenge 2021 (AICITY21). The Track2 is a vehicle re-identification (ReID) task with both the real-world data and synt…
Event-Aware Instructed Assistant for Referring Video Segmentation
Jinyu Liu, Henghui Ding, Shuting He +1
Existing referring video segmentation methods often treat a video as a single event consisting of multiple images, overlooking the fact that a video typically contains multiple dis…
SCORE: Scene Context Matters in Open-Vocabulary Remote Sensing Instance Segmentation
Shiqi Huang, Shuting He, Huaiyuan Qin +1
Most existing remote sensing instance segmentation approaches are designed for close-vocabulary prediction, limiting their ability to recognize novel categories or generalize acros…
Wearable Device-Based Real-Time Monitoring of Physiological Signals: Evaluating Cognitive Load Across Different Tasks
Ling He, Yanxin Chen, Wenqi Wang +2
This study employs cutting-edge wearable monitoring technology to conduct high-precision, high-temporal-resolution (1-second interval) cognitive load assessment on electroencephalo…
GroundFlow: A Plug-in Module for Temporal Reasoning on 3D Point Cloud Sequential Grounding
Zijun Lin, Shuting He, Cheston Tan +1
Sequential grounding in 3D point clouds (SG3D) refers to locating sequences of objects by following text instructions for a daily activity with detailed steps. Current 3D visual gr…
Hierarchical Alignment-enhanced Adaptive Grounding Network for Generalized Referring Expression Comprehension
Yaxian Wang, Henghui Ding, Shuting He +3
In this work, we address the challenging task of Generalized Referring Expression Comprehension (GREC). Compared to the classic Referring Expression Comprehension (REC) that focuse…
RefMask3D: Language-Guided Transformer for 3D Referring Segmentation
Shuting He, Henghui Ding
3D referring segmentation is an emerging and challenging vision-language task that aims to segment the object described by a natural language expression in a point cloud scene. The…
GREC: Generalized Referring Expression Comprehension
Shuting He, Henghui Ding, Chang Liu +1
The objective of Classic Referring Expression Comprehension (REC) is to produce a bounding box corresponding to the object mentioned in a given textual description. Commonly, exist…
FantasyStyle: Controllable Stylized Distillation for 3D Gaussian Splatting
Yitong Yang, Yinglin Wang, Changshuo Wang +2
The success of 3DGS in generative and editing applications has sparked growing interest in 3DGS-based style transfer. However, current methods still face two major challenges: (1)…
VGSG: Vision-Guided Semantic-Group Network for Text-based Person Search
Shuting He, Hao Luo, Wei Jiang +2
Text-based Person Search (TBPS) aims to retrieve images of target pedestrian indicated by textual descriptions. It is essential for TBPS to extract fine-grained local features and…
Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation
Shuting He, Henghui Ding
Referring video segmentation relies on natural language expressions to identify and segment objects, often emphasizing motion clues. Previous works treat a sentence as a whole and…
Prototype Adaption and Projection for Few- and Zero-shot 3D Point Cloud Semantic Segmentation
Shuting He, Xudong Jiang, Wei Jiang +1
In this work, we address the challenging task of few-shot and zero-shot 3D point cloud semantic segmentation. The success of few-shot semantic segmentation in 2D computer vision is…
MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions
Henghui Ding, Chang Liu, Shuting He +2
This paper strives for motion expressions guided video segmentation, which focuses on segmenting objects in video content based on a sentence describing the motion of the objects.…
Primitive Generation and Semantic-related Alignment for Universal Zero-Shot Segmentation
Shuting He, Henghui Ding, Wei Jiang
We study universal zero-shot segmentation in this work to achieve panoptic, instance, and semantic segmentation for novel categories without any training samples. Such zero-shot se…
TransReID: Transformer-based Object Re-Identification
Shuting He, Hao Luo, Pichao Wang +3
Extracting robust feature representation is one of the key challenges in object re-identification (ReID). Although convolution neural network (CNN)-based methods have achieved grea…
Taylor Series-Inspired Local Structure Fitting Network for Few-shot Point Cloud Semantic Segmentation
Changshuo Wang, Shuting He, Xiang Fang +3
Few-shot point cloud semantic segmentation aims to accurately segment "unseen" new categories in point cloud scenes using limited labeled data. However, pretraining-based methods n…
MOSE: A New Dataset for Video Object Segmentation in Complex Scenes
Henghui Ding, Chang Liu, Shuting He +3
Video object segmentation (VOS) aims at segmenting a particular object throughout the entire video clip sequence. The state-of-the-art VOS methods have achieved excellent performan…
Multi-Domain Learning and Identity Mining for Vehicle Re-Identification
Shuting He, Hao Luo, Weihua Chen +5
This paper introduces our solution for the Track2 in AI City Challenge 2020 (AICITY20). The Track2 is a vehicle re-identification (ReID) task with both the real-world data and synt…
1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification
Jianyang Gu, Hao Luo, Weihua Chen +6
This paper presents our proposed methods for domain adaptive pedestrian re-identification (Re-ID) task in Visual Domain Adaptation Challenge (VisDA-2020). Considering the large gap…
DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment
Hao Wang, Licheng Pan, Yuan Lu +7
Training time-series forecasting models requires aligning the conditional distribution of model forecasts with that of the label sequence. The standard direct forecast (DF) approac…
PVUW 2024 Challenge on Complex Video Understanding: Methods and Results
Henghui Ding, Chang Liu, Yunchao Wei +34
Pixel-level Video Understanding in the Wild Challenge (PVUW) focus on complex video understanding. In this CVPR 2024 workshop, we add two new tracks, Complex Video Object Segmentat…
DiffStyle3D: Consistent 3D Gaussian Stylization via Attention Optimization
Yitong Yang, Xuexin Liu, Yinglin Wang +4
3D style transfer enables the creation of visually expressive 3D content, enriching the visual appearance of 3D scenes and objects. However, existing VGG- and CLIP-based methods st…