Papers Point Tracking
“Point Tracking” 태그가 달린 논문 234편 · 필터 해제
TrackEverything: Long Horizon Dense Tracking via De-Duplicating 3D Scene Representations
Existing point tracking models face a fundamental tradeoff: they can either track a sparse set of query points over long horizons, or track all points across only short clips. We introduce TrackEverything, a 3D point tra…
Point TrackingAn LLM-Driven Workflow for Automated Process Control Strategy Generation and Tuning from Dynamic Process Models
We present a structured large-language-model-driven workflow for automated multi-variable control design from dynamic process models. The workflow decomposes the design task into constrained code-generation steps: plant-…
Code GenerationPoint TrackingFoMoVLA: Bridging Visual Foresight and Motion Guidance for Vision-Language-Action Models
Vision-Language-Action (VLA) models have achieved impressive results in visuomotor policy learning, yet remain fundamentally reactive, mapping current observations and language to actions without explicit forward predict…
Zero-shot GeneralizationPoint TrackingMotion-Conditioned Multi-View Fusion for Myocardial Infarction Localization from Echocardiography
Myocardial infarction (MI) remains a leading cause of mortality worldwide. Echocardiography (Echo) is a widely available modality for MI assessment, where regional wall motion abnormality is a key indicator. Prior learni…
Point TrackingOmniX: Any-view and Any-time 4D Reconstruction via Feed-forward Trajectory Fields
Previous feed-forward 4D reconstruction methods either predict per-frame static point clouds, ignoring foreground motion, or estimate point cloud trajectories while being limited to small camera motions. This restricts t…
Camera Pose EstimationTrajectory PredictionDepth EstimationPoint TrackingEgo-Human Motion Prediction with 3D-Aware LLM
Anticipating human motion from an egocentric perspective is fundamental for proactive assistance in AR/VR, human-robot collaboration, and embodied AI. While recent works incorporate language as a semantic prior to reduce…
Motion ForecastingPoint TrackingMonocular Vision Based Control Framework for Grasping
Grasping in unstructured environments requires handling objects with widely different mechanical properties, from soft and deformable items to rigid everyday objects. Most existing approaches address these categories sep…
Monocular Depth EstimationImage SegmentationObject DetectionPoint TrackingMVTrack4Gen: Multi-View Point Tracking as Geometric Supervision for 4D Video Generation
Synthesizing a novel-view video from a monocular reference video along a target camera trajectory requires both geometric consistency and motion fidelity with respect to the reference video. Existing methods based on exp…
Video GenerationPoint TrackingISOPoT: Imaging Sonar Odometry by Point Tracking
Reliable navigation in underwater environments remains a key challenge in marine robotics. In such scenarios, forward-looking sonars are a natural choice for long-range perception, offering wide coverage even in turbid, …
Keypoint DetectionPoint TrackingLow-power analogue neural networks with trainable nonlinear connections for continuous control
Physical neural networks promise low-power machine learning by computing directly with analogue device physics, but most architectures force nonlinear device responses to act as scalar weights. Inspired by Kolmogorov-Arn…
Continuous ControlPoint TrackingGo-with-the-Track: Video Compositing and Motion Control with Point Tracking
Filmmaking demands precise motion control and reference image compositing -- capabilities that existing methods treat separately. Point-track-conditioned image-to-video models restrict content insertion to the first fram…
Video GenerationPoint TrackingBackward Coherence and Hidden-State Stability in Recurrent Neural Networks: A Quasi-Reverse-Martingale Theory
Recurrent neural networks maintain a hidden state $h_t$, but its probabilistic meaning is often unclear. We study hidden-state stability through \emph{backward coherence}: the extent to which $h_t$ can be reconstructed f…
Human Activity RecognitionPoint TrackingRevisiting Articulated Parts Perception in Robot Manipulation
We are surrounded by various objects with movable, articulated parts, e.g., box, handle, door. An accurate and generalizable perception of articulated parts is essential to enhance robotic manipulation capabilities. Buil…
Robot ManipulationPoint Tracking4D Reconstruction from Sparse Dynamic Cameras
Although dynamic 3D (i.e., 4D) reconstruction from a monocular dynamic camera has recently advanced, it remains fundamentally limited by depth ambiguity. In this paper, we focus on an alternative practical way, i.e., spa…
Point TrackingLearning Global Motion with Compact Gaussians for Feed-Forward 4D Reconstruction
Dynamic scene reconstruction from monocular video remains a fundamental challenge in computer vision. Existing feed-forward methods predict 3D Gaussians pixel-wise for each frame, suffering from duplicated Gaussians and …
Scene UnderstandingPoint TrackingTraining-Free Object-Agnostic Jam Detection in Fulfillment Centers
In fulfillment centers, diverse objects move continuously from inbound to outbound operations and can become jammed due to excessive conveyor friction, incorrect orientation, or mechanical failures. Traditional jam detec…
Object DetectionPoint TrackingMotion-guided sparse correction enables expert-quality point tracking across diverse microscopy regimes
Tracking the dynamics of non-canonical biological systems in microscopy videos remains a persistent challenge. Both classical and learning-based trackers depend on expert-reviewed data to be evaluated and adapted, yet ex…
Point TrackingPoint Tracking Improves World Action Models
Robot policy learning benefits from world-action models that capture environment dynamics, but pixel-level prediction entangles dynamics with nuisance factors such as lighting and texture, making learned representations …
Point TrackingArticulation in Prime: Primitive-Based Articulated Object Understanding from a Single Casual Video
Retrieving the 3D kinematics of articulated objects from monocular video is a fundamental challenge in computer vision. Existing methods rely on complex video setups or cues such as long-term point tracking or wide-basel…
Point TrackingMotion Cues from Image-based Point Tracking for LiDAR Scene Flow Estimation
LiDAR scene flow estimation is essential for autonomous driving, as it provides 3D motion for each point. Self-supervised approaches use static-dynamic classification to mitigate the imbalance between static and dynamic …
Self-supervised Scene Flow EstimationAutonomous DrivingPoint Tracking