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Found 8 papers, 3 papers with code
BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Models
Now text-to-image foundation models are widely applied to various downstream image synthesis tasks, such as controllable image generation and image editing, while downstream video synthesis tasks are less explored for several reasons.
DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance
Especially for fidelity, our model has a powerful image retention ability and delivers the best results in UCF101 compared to other image-to-video models to our best knowledge.
VideoAssembler: Identity-Consistent Video Generation with Reference Entities using Diffusion Model
Identity-consistent video generation seeks to synthesize videos that are guided by both textual prompts and reference images of entities.
Ranked #1 on
Video Generation
on MSR-VTT
Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models
In this way, temporal consistency can be kept with video LDM while high-fidelity from the image LDM can also be exploited.
Reuse and Diffuse: Iterative Denoising for Text-to-Video Generation
Conditioned on an initial video clip with a small number of frames, additional frames are iteratively generated by reusing the original latent features and following the previous diffusion process.
Towards Universal Vision-language Omni-supervised Segmentation
To improve the open-world segmentation ability, we leverage omni-supervised data (i. e., panoptic segmentation data, object detection data, and image-text pairs data) into training, thus enriching the open-world segmentation ability and achieving better segmentation accuracy.
PIDRo: Parallel Isomeric Attention with Dynamic Routing for Text-Video Retrieval
The parallel isomeric attention module is used as the video encoder, which consists of two parallel branches modeling the spatial-temporal information of videos from both patch and frame levels.
Ranked #3 on
Video Retrieval
on MSR-VTT-1kA
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark
Experiments show that Wukong can serve as a promising Chinese pre-training dataset and benchmark for different cross-modal learning methods.
Ranked #6 on
Image Retrieval
on MUGE Retrieval
