Papers Scene Flow Estimation
“Scene Flow Estimation” 태그가 달린 논문 166편 · 필터 해제
RVLoss: Runoff Vote Loss for Self-Supervised LiDAR Scene Flow Estimation
LiDAR scene flow estimates point-wise motion between two consecutive scans, referred to as the source and target. Leading self-supervised methods typically minimize the Chamfer loss, the nearest neighbor distance between…
Self-Supervised LearningScene Flow EstimationDisFlow: Scene Flow from Distance Field for Object Pose, Velocity Tracking, and Dynamic Object Reconstruction
We present \emph{DisFlow}, a novel framework for online scene flow estimation from distance field that enables \emph{6DoF dynamic object pose estimation}, \emph{motion tracking}, and \emph{surface reconstruction}. The sc…
Scene Flow EstimationPose EstimationWeakly Supervised Cross-Modal Learning for 4D Radar Scene Flow Estimation
Due to the difficulty of obtaining ground-truth data for 4D radar scene flow estimation, previous methods typically rely on either self-supervised losses or cross-modal supervision using 3D LiDAR data, 2D images, and odo…
3D Multi-Object TrackingScene Flow EstimationPoint CloudsRAFT-MSF++: Temporal Geometry-Motion Feature Fusion for Self-Supervised Monocular Scene Flow
Monocular scene flow estimation aims to recover dense 3D motion from image sequences, yet most existing methods are limited to two-frame inputs, restricting temporal modeling and robustness to occlusions. We propose RAFT…
Scene Flow EstimationSynFlow: Scaling Up LiDAR Scene Flow Estimation with Synthetic Data
Reliable 3D dynamic perception requires models that can anticipate motion beyond predefined categories, yet progress is hindered by the scarcity of dense, high-quality motion annotations. While self-supervision on unlabe…
Scene Flow EstimationPCSTracker: Long-Term Scene Flow Estimation for Point Cloud Sequences
Point cloud scene flow estimation is fundamental to long-term and fine-grained 3D motion analysis. However, existing methods are typically limited to pairwise settings and struggle to maintain temporal consistency over l…
Scene Flow EstimationSF3D-RGB: Scene Flow Estimation from Monocular Camera and Sparse LiDAR
Scene flow estimation is an extremely important task in computer vision to support the perception of dynamic changes in the scene. For robust scene flow, learning-based approaches have recently achieved impressive result…
Scene Flow EstimationGraph MatchingPoint CloudsTeFlow: Enabling Multi-frame Supervision for Self-Supervised Feed-forward Scene Flow Estimation
Self-supervised feed-forward methods for scene flow estimation offer real-time efficiency, but their supervision from two-frame point correspondences is unreliable and often breaks down under occlusions. Multi-frame supe…
Scene Flow EstimationMotionCrafter: Dense Geometry and Motion Reconstruction with a 4D VAE
We present MotionCrafter, a framework that leverages video generators to jointly reconstruct 4D geometry and estimate dense motion from a monocular video. The key idea is a joint representation of dense 3D point maps and…
Scene Flow EstimationAsyncBEV: Cross-modal Flow Alignment in Asynchronous 3D Object Detection
In autonomous driving, multi-modal perception tasks like 3D object detection typically rely on well-synchronized sensors, both at training and inference. However, despite the use of hardware- or software-based synchroniz…
Scene Flow Estimation3D Object DetectionAutonomous DrivingRaLiFlow: Scene Flow Estimation with 4D Radar and LiDAR Point Clouds
Recent multimodal fusion methods, integrating images with LiDAR point clouds, have shown promise in scene flow estimation. However, the fusion of 4D millimeter wave radar and LiDAR remains unexplored. Unlike LiDAR, radar…
Scene Flow EstimationPoint CloudsDoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance
Accurate 3D scene flow estimation is critical for autonomous systems to navigate dynamic environments safely, but creating the necessary large-scale, manually annotated datasets remains a significant bottleneck for devel…
Scene Flow EstimationDeltaFlow: An Efficient Multi-frame Scene Flow Estimation Method
Previous dominant methods for scene flow estimation focus mainly on input from two consecutive frames, neglecting valuable information in the temporal domain. While recent trends shift towards multi-frame reasoning, they…
Domain GeneralizationScene Flow EstimationMoVieS: Motion-Aware 4D Dynamic View Synthesis in One Second
We present MoVieS, a novel feed-forward model that synthesizes 4D dynamic novel views from monocular videos in one second. MoVieS represents dynamic 3D scenes using pixel-aligned grids of Gaussian primitives, explicitly …
Novel View SynthesisPoint TrackingScene Flow EstimationSemantic SegmentationVISC: mmWave Radar Scene Flow Estimation using Pervasive Visual-Inertial Supervision
This work proposes a mmWave radar's scene flow estimation framework supervised by data from a widespread visual-inertial (VI) sensor suite, allowing crowdsourced training data from smart vehicles. Current scene flow esti…
Scene Flow EstimationPoint CloudsKDMOS:Knowledge Distillation for Motion Segmentation
Motion Object Segmentation (MOS) is crucial for autonomous driving, as it enhances localization, path planning, map construction, scene flow estimation, and future state prediction. While existing methods achieve strong …
Autonomous DrivingKnowledge DistillationMotion SegmentationScene Flow Estimation+1VoxelSplat: Dynamic Gaussian Splatting as an Effective Loss for Occupancy and Flow Prediction
Recent advancements in camera-based occupancy prediction have focused on the simultaneous prediction of 3D semantics and scene flow, a task that presents significant challenges due to specific difficulties, e.g., occlusi…
Scene Flow EstimationEstimating Scene Flow in Robot Surroundings with Distributed Miniaturized Time-of-Flight Sensors
Tracking motions of humans or objects in the surroundings of the robot is essential to improve safe robot motions and reactions. In this work, we present an approach for scene flow estimation from low-density and noisy p…
Scene Flow EstimationVoteFlow: Enforcing Local Rigidity in Self-Supervised Scene Flow
Scene flow estimation aims to recover per-point motion from two adjacent LiDAR scans. However, in real-world applications such as autonomous driving, points rarely move independently of others, especially for nearby poin…
Autonomous DrivingComputational EfficiencyInductive BiasScene Flow Estimation+1Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction
DUSt3R has recently shown that one can reduce many tasks in multi-view geometry, including estimating camera intrinsics and extrinsics, reconstructing the scene in 3D, and establishing image correspondences, to the predi…
3D Object Tracking3D ReconstructionDepth EstimationDepth Prediction+5