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Found 8 papers, 4 papers with code
GFlow: Recovering 4D World from Monocular Video
To this end, we introduce GFlow, a new framework that utilizes only 2D priors (depth and optical flow) to lift a video (3D) to a 4D explicit representation, entailing a flow of Gaussian splatting through space and time.
DragGaussian: Enabling Drag-style Manipulation on 3D Gaussian Representation
User-friendly 3D object editing is a challenging task that has attracted significant attention recently.
Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction
We tackle the challenge of efficiently reconstructing a 3D asset from a single image at millisecond speed.
Anything-3D: Towards Single-view Anything Reconstruction in the Wild
3D reconstruction from a single-RGB image in unconstrained real-world scenarios presents numerous challenges due to the inherent diversity and complexity of objects and environments.
Context-aware Visual Tracking with Joint Meta-updating
These deep trackers usually do not perform online update or update single sub-branch of the tracking model, for which they cannot adapt to the appearance variation of objects.
Unsupervised Learning of Accurate Siamese Tracking
As unlimited self-supervision signals can be obtained by tracking a video along a cycle in time, we investigate evolving a Siamese tracker by tracking videos forward-backward.
Backbone is All Your Need: A Simplified Architecture for Visual Object Tracking
Exploiting a general-purpose neural architecture to replace hand-wired designs or inductive biases has recently drawn extensive interest.
An Informative Tracking Benchmark
Along with the rapid progress of visual tracking, existing benchmarks become less informative due to redundancy of samples and weak discrimination between current trackers, making evaluations on all datasets extremely time-consuming.
