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Found 9 papers, 3 papers with code
GS-DiT: Advancing Video Generation with Pseudo 4D Gaussian Fields through Efficient Dense 3D Point Tracking
Specifically, we propose a novel framework that constructs a pseudo 4D Gaussian field with dense 3D point tracking and renders the Gaussian field for all video frames.
A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding
We integrate pose embedding to encapsulate information such as multi-view camera poses, providing implicit geometric constraints for multi-view disparity feature fusion dominated by attention.
BlinkVision: A Benchmark for Optical Flow, Scene Flow and Point Tracking Estimation using RGB Frames and Events
BlinkVision enables extensive benchmarks on three types of correspondence tasks (optical flow, point tracking, and scene flow estimation) for both image-based and event-based methods, offering new observations, practices, and insights for future research.
Phased Consistency Models
In this paper, we identify three key flaws in the current design of Latent Consistency Models (LCMs).
AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data
This paper introduces an effective method for computation-efficient personalized style video generation without requiring access to any personalized video data.
Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling
For the first stage, we propose a diffusion-based motion field predictor, which focuses on deducing the trajectories of the reference image's pixels.
Context-PIPs: Persistent Independent Particles Demands Spatial Context Features
We tackle the problem of Persistent Independent Particles (PIPs), also called Tracking Any Point (TAP), in videos, which specifically aims at estimating persistent long-term trajectories of query points in videos.
VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation
We first propose a TRi-frame Optical Flow (TROF) module that estimates bi-directional optical flows for the center frame in a three-frame manner.
NeuralMarker: A Framework for Learning General Marker Correspondence
We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker.
