369 citations · 458 across the 27 of their papers we have counts for
22 papers · 1 filter
ReasonCLIP-58M: Visually Grounded Commonsense Reasoning Supervision for CLIP
Sicheng Zhang, Muzammal Naseer, Binzhu Xie +5
CLIP and its variants are widely adopted visual backbones in multimodal systems, but their pretraining remains dominated by descriptive image-text alignment. As downstream applicat…
EgoHandICL: Egocentric 3D Hand Reconstruction with In-Context Learning
Binzhu Xie, Shi Qiu, Sicheng Zhang +5
Robust 3D hand reconstruction in egocentric vision is challenging due to depth ambiguity, self-occlusion, and complex hand-object interactions. Prior methods mitigate these issues…
COS3D: Collaborative Open-Vocabulary 3D Segmentation
Runsong Zhu, Ka-Hei Hui, Zhengzhe Liu +5
Open-vocabulary 3D segmentation is a fundamental yet challenging task, requiring a mutual understanding of both segmentation and language. However, existing Gaussian-splatting-base…
Trade-offs in Image Generation: How Do Different Dimensions Interact?
Sicheng Zhang, Binzhu Xie, Zhonghao Yan +7
Model performance in text-to-image (T2I) and image-to-image (I2I) generation often depends on multiple aspects, including quality, alignment, diversity, and robustness. However, mo…
ClipGS: Clippable Gaussian Splatting for Interactive Cinematic Visualization of Volumetric Medical Data
Chengkun Li, Yuqi Tong, Kai Chen +6
The visualization of volumetric medical data is crucial for enhancing diagnostic accuracy and improving surgical planning and education. Cinematic rendering techniques significantl…
NoiseSDF2NoiseSDF: Learning Clean Neural Fields from Noisy Supervision
Tengkai Wang, Weihao Li, Ruikai Cui +2
Reconstructing accurate implicit surface representations from point clouds remains a challenging task, particularly when data is captured using low-quality scanning devices. These…
Rethinking End-to-End 2D to 3D Scene Segmentation in Gaussian Splatting
Runsong Zhu, Shi Qiu, Zhengzhe Liu +4
Lifting multi-view 2D instance segmentation to a radiance field has proven to be effective to enhance 3D understanding. Existing methods rely on direct matching for end-to-end lift…
Creating Virtual Environments with 3D Gaussian Splatting: A Comparative Study
Shi Qiu, Binzhu Xie, Qixuan Liu +1
3D Gaussian Splatting (3DGS) has recently emerged as an innovative and efficient 3D representation technique. While its potential for extended reality (XR) applications is frequent…
MS2Mesh-XR: Multi-modal Sketch-to-Mesh Generation in XR Environments
Yuqi Tong, Yue Qiu, Ruiyang Li +2
We present MS2Mesh-XR, a novel multi-modal sketch-to-mesh generation pipeline that enables users to create realistic 3D objects in extended reality (XR) environments using hand-dra…
Advancing Extended Reality with 3D Gaussian Splatting: Innovations and Prospects
Shi Qiu, Binzhu Xie, Qixuan Liu +1
3D Gaussian Splatting (3DGS) has attracted significant attention for its potential to revolutionize 3D representation, rendering, and interaction. Despite the rapid growth of 3DGS…
NumGrad-Pull: Numerical Gradient Guided Tri-plane Representation for Surface Reconstruction from Point Clouds
Ruikai Cui, Binzhu Xie, Shi Qiu +3
Reconstructing continuous surfaces from unoriented and unordered 3D points is a fundamental challenge in computer vision and graphics. Recent advancements address this problem by t…
PCF-Lift: Panoptic Lifting by Probabilistic Contrastive Fusion
Runsong Zhu, Shi Qiu, Qianyi Wu +3
Panoptic lifting is an effective technique to address the 3D panoptic segmentation task by unprojecting 2D panoptic segmentations from multi-views to 3D scene. However, the quality…
Adaptive Low Rank Adaptation of Segment Anything to Salient Object Detection
Ruikai Cui, Siyuan He, Shi Qiu
Foundation models, such as OpenAI's GPT-3 and GPT-4, Meta's LLaMA, and Google's PaLM2, have revolutionized the field of artificial intelligence. A notable paradigm shift has been t…
P2C: Self-Supervised Point Cloud Completion from Single Partial Clouds
Ruikai Cui, Shi Qiu, Saeed Anwar +4
Point cloud completion aims to recover the complete shape based on a partial observation. Existing methods require either complete point clouds or multiple partial observations of…
PointCaM: Cut-and-Mix for Open-Set Point Cloud Learning
Jie Hong, Shi Qiu, Weihao Li +4
Point cloud learning is receiving increasing attention. However, most existing point cloud models lack the practical ability to deal with the unavoidable presence of unknown object…
Energy-Based Residual Latent Transport for Unsupervised Point Cloud Completion
Ruikai Cui, Shi Qiu, Saeed Anwar +2
Unsupervised point cloud completion aims to infer the whole geometry of a partial object observation without requiring partial-complete correspondence. Differing from existing dete…
Semi-signed prioritized neural fitting for surface reconstruction from unoriented point clouds
Runsong Zhu, Di Kang, Ka-Hei Hui +6
Reconstructing 3D geometry from \emph{unoriented} point clouds can benefit many downstream tasks. Recent shape modeling methods mostly adopt implicit neural representation to fit a…
PU-Transformer: Point Cloud Upsampling Transformer
Shi Qiu, Saeed Anwar, Nick Barnes
Given the rapid development of 3D scanners, point clouds are becoming popular in AI-driven machines. However, point cloud data is inherently sparse and irregular, causing significa…
PnP-3D: A Plug-and-Play for 3D Point Clouds
Shi Qiu, Saeed Anwar, Nick Barnes
With the help of the deep learning paradigm, many point cloud networks have been invented for visual analysis. However, there is great potential for development of these networks s…
Investigating Attention Mechanism in 3D Point Cloud Object Detection
Shi Qiu, Yunfan Wu, Saeed Anwar +1
Object detection in three-dimensional (3D) space attracts much interest from academia and industry since it is an essential task in AI-driven applications such as robotics, autonom…
Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion
Shi Qiu, Saeed Anwar, Nick Barnes
Given the prominence of current 3D sensors, a fine-grained analysis on the basic point cloud data is worthy of further investigation. Particularly, real point cloud scenes can intu…
Dense-Resolution Network for Point Cloud Classification and Segmentation
Shi Qiu, Saeed Anwar, Nick Barnes
Point cloud analysis is attracting attention from Artificial Intelligence research since it can be widely used in applications such as robotics, Augmented Reality, self-driving. Ho…