4 citations · 5 across the 25 of their papers we have counts for
27 papers
WildHSR: Metric Feed-Forward 4D People-Scene Reconstruction from a 3D Foundation Model
Jerrin Bright, John Zelek
3D foundation models recover video cameras and geometry in one forward pass, but some of the strongest are up to scale. Joint people-scene reconstruction then requires two missing…
iVISION-2DCD: A Long-Term Change Detection Dataset for Large-Scale Outdoor Construction Monitoring
Dayou Mao, Yuchen Lin, Ashkan Ebadi +3
Automation in construction is essential for reducing costs and human errors in large-scale projects. We approach the construction progress monitoring from the aspect of detecting c…
CoGS: Compositional Dynamic Human-Object Scenes Gaussian Splatting from Monocular Video
Jerrin Bright, John Zelek
Reconstructing dynamic human--object interaction scenes from monocular video is difficult because the human, manipulated object, and background obey different motion models while s…
Latent Space Reinforcement Learning for Inverse Material Estimation in Food Fracture Simulation
Adrian Ramlal, Yuhao Chen, John S. Zelek
Realistic visual simulation of food manipulation requires accurate material parameters, yet these are difficult to measure directly and vary across the heterogeneous regions of a s…
PersistGS: Differentiable Physics for Object Permanence in 4D Gaussian Splatting
Adrian Ramlal, John S. Zelek
Dynamic 3D Gaussian Splatting (3DGS) methods reconstruct time-varying scenes from synchronized multi-camera video using photometric supervision. When a moving object becomes fully…
Beyond Static Gaussians: An Empirical Investigation of Architectural Paradigms for Dynamic 3D Scene Reconstruction
Adrian Ramlal, John S. Zelek
Dynamic scene reconstruction via 3D Gaussian Splatting (3DGS) has emerged as a compelling approach for representing evolving environments, yet understanding trade-offs between meth…
Optimizing 3D Gaussian Splatting via Point Cloud Upsampling
Adrian Ramlal, Yan Song Hu, John S. Zelek
3D Gaussian Splatting (3DGS) is a technique for creating and rendering 3D scenes, however its performance depends heavily on the quality of initial seed points. To improve 3DGS ini…
Real-Time Physics Simulation with Dynamic Mesh-Gaussian Reconstructions
Adrian Ramlal, John S. Zelek
Integrating dynamic 3D reconstructions into physics simulation requires fixed mesh topology for efficient collision detection, but state-of-the-art methods like DG-Mesh produce var…
Interpretable Pre-Release Baseball Pitch Type Anticipation from Broadcast 3D Kinematics
Jerrin Bright, Michelle Lu, John Zelek
How much can a pitcher's body reveal about the upcoming pitch? We study this question at scale by classifying eight pitch types from monocular 3D pose sequences, without access to…
Scalable Injury-Risk Screening in Baseball Pitching From Broadcast Video
Jerrin Bright, Justin Mende, John Zelek
Injury prediction in pitching depends on precise biomechanical signals, yet gold-standard measurements come from expensive, stadium-installed multi-camera systems that are unavaila…
Avatar4D: Synthesizing Domain-Specific 4D Humans for Real-World Pose Estimation
Jerrin Bright, Zhibo Wang, Dmytro Klepachevskyi +4
We present Avatar4D, a real-world transferable pipeline for generating customizable synthetic human motion datasets tailored to domain-specific applications. Unlike prior works, wh…
DreamPose3D: Hallucinative Diffusion with Prompt Learning for 3D Human Pose Estimation
Jerrin Bright, Yuhao Chen, John S. Zelek
Accurate 3D human pose estimation remains a critical yet unresolved challenge, requiring both temporal coherence across frames and fine-grained modeling of joint relationships. How…
Ice Hockey Puck Localization Using Contextual Cues
Liam Salass, Jerrin Bright, Amir Nazemi +3
Puck detection in ice hockey broadcast videos poses significant challenges due to the puck's small size, frequent occlusions, motion blur, broadcast artifacts, and scale inconsiste…
Gen4D: Synthesizing Humans and Scenes in the Wild
Jerrin Bright, Zhibo Wang, Yuhao Chen +3
Lack of input data for in-the-wild activities often results in low performance across various computer vision tasks. This challenge is particularly pronounced in uncommon human-cen…
SportMamba: Adaptive Non-Linear Multi-Object Tracking with State Space Models for Team Sports
Dheeraj Khanna, Jerrin Bright, Yuhao Chen +1
Multi-object tracking (MOT) in team sports is particularly challenging due to the fast-paced motion and frequent occlusions resulting in motion blur and identity switches, respecti…
SplatPose+: Real-time Image-Based Pose-Agnostic 3D Anomaly Detection
Yizhe Liu, Yan Song Hu, Yuhao Chen +1
Image-based Pose-Agnostic 3D Anomaly Detection is an important task that has emerged in industrial quality control. This task seeks to find anomalies from query images of a tested…
MGSO: Monocular Real-time Photometric SLAM with Efficient 3D Gaussian Splatting
Yan Song Hu, Nicolas Abboud, Muhammad Qasim Ali +5
Real-time SLAM with dense 3D mapping is computationally challenging, especially on resource-limited devices. The recent development of 3D Gaussian Splatting (3DGS) offers a promisi…
Towards Real-Time Gaussian Splatting: Accelerating 3DGS through Photometric SLAM
Yan Song Hu, Dayou Mao, Yuhao Chen +1
Initial applications of 3D Gaussian Splatting (3DGS) in Visual Simultaneous Localization and Mapping (VSLAM) demonstrate the generation of high-quality volumetric reconstructions f…
Dense Monocular Motion Segmentation Using Optical Flow and Pseudo Depth Map: A Zero-Shot Approach
Yuxiang Huang, Yuhao Chen, John Zelek
Motion segmentation from a single moving camera presents a significant challenge in the field of computer vision. This challenge is compounded by the unknown camera movements and t…
Multi Player Tracking in Ice Hockey with Homographic Projections
Harish Prakash, Jia Cheng Shang, Ken M. Nsiempba +3
Multi Object Tracking (MOT) in ice hockey pursues the combined task of localizing and associating players across a given sequence to maintain their identities. Tracking players fro…
PitcherNet: Powering the Moneyball Evolution in Baseball Video Analytics
Jerrin Bright, Bavesh Balaji, Yuhao Chen +2
In the high-stakes world of baseball, every nuance of a pitcher's mechanics holds the key to maximizing performance and minimizing runs. Traditional analysis methods often rely on…
Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep Learning with Geometric Motion Model Fusion
Yuxiang Huang, Yuhao Chen, John Zelek
Detecting and segmenting moving objects from a moving monocular camera is challenging in the presence of unknown camera motion, diverse object motions and complex scene structures.…
Domain-Guided Masked Autoencoders for Unique Player Identification
Bavesh Balaji, Jerrin Bright, Sirisha Rambhatla +4
Unique player identification is a fundamental module in vision-driven sports analytics. Identifying players from broadcast videos can aid with various downstream tasks such as play…
Distribution and Depth-Aware Transformers for 3D Human Mesh Recovery
Jerrin Bright, Bavesh Balaji, Harish Prakash +3
Precise Human Mesh Recovery (HMR) with in-the-wild data is a formidable challenge and is often hindered by depth ambiguities and reduced precision. Existing works resort to either…