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Found 13 papers, 5 papers with code
HumanVid: Demystifying Training Data for Camera-controllable Human Image Animation
Moreover, these approaches prioritize 2D human motion and overlook the significance of camera motions in videos, leading to limited control and unstable video generation.
Fast and Efficient: Mask Neural Fields for 3D Scene Segmentation
Recent advancements in distilling 2D vision-language foundation models into neural fields, like NeRF and 3DGS, enables open-vocabulary segmentation of 3D scenes from 2D multi-view images without the need for precise 3D annotations.
Technique Report of CVPR 2024 PBDL Challenges
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies.
Multiplane Prior Guided Few-Shot Aerial Scene Rendering
By investigating NeRF's and Multiplane Image (MPI)'s behavior, we propose to guide the training process of NeRF with a Multiplane Prior.
Edit-Your-Motion: Space-Time Diffusion Decoupling Learning for Video Motion Editing
In the first training stage, we focus on learning the spatial features (the features of object content) and breaking down the temporal relationships in the video frames by shuffling them.
CameraCtrl: Enabling Camera Control for Text-to-Video Generation
Controllability plays a crucial role in video generation since it allows users to create desired content.
Transferring Modality-Aware Pedestrian Attentive Learning for Visible-Infrared Person Re-identification
Visible-infrared person re-identification (VI-ReID) aims to search the same pedestrian of interest across visible and infrared modalities.
SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models
The development of text-to-video (T2V), i. e., generating videos with a given text prompt, has been significantly advanced in recent years.
LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models
To this end, we propose LaVie, an integrated video generation framework that operates on cascaded video latent diffusion models, comprising a base T2V model, a temporal interpolation model, and a video super-resolution model.
Ranked #4 on
Text-to-Video Generation
on EvalCrafter Text-to-Video (ECTV) Dataset
(using extra training data)
AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning
Once trained, the motion module can be inserted into a personalized T2I model to form a personalized animation generator.
Dynamic Storyboard Generation in an Engine-based Virtual Environment for Video Production
Amateurs working on mini-films and short-form videos usually spend lots of time and effort on the multi-round complicated process of setting and adjusting scenes, plots, and cameras to deliver satisfying video shots.
Temporal and Contextual Transformer for Multi-Camera Editing of TV Shows
The ability to choose an appropriate camera view among multiple cameras plays a vital role in TV shows delivery.
More Separable and Easier to Segment: A Cluster Alignment Method for Cross-Domain Semantic Segmentation
Feature alignment between domains is one of the mainstream methods for Unsupervised Domain Adaptation (UDA) semantic segmentation.
