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Found 19 papers, 10 papers with code
Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models
A primary limitation is the substantial number of image tokens required for AR models, which constrains both training and inference efficiency, as well as image resolution.
Cobra: Efficient Line Art COlorization with BRoAder References
The comic production industry requires reference-based line art colorization with high accuracy, efficiency, contextual consistency, and flexible control.
FullDiT: Multi-Task Video Generative Foundation Model with Full Attention
Current video generative foundation models primarily focus on text-to-video tasks, providing limited control for fine-grained video content creation.
VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control
Video inpainting, which aims to restore corrupted video content, has experienced substantial progress.
ColorFlow: Retrieval-Augmented Image Sequence Colorization
Automatic black-and-white image sequence colorization while preserving character and object identity (ID) is a complex task with significant market demand, such as in cartoon or comic series colorization.
BrushEdit: All-In-One Image Inpainting and Editing
Image editing has advanced significantly with the development of diffusion models using both inversion-based and instruction-based methods.
Pay Attention and Move Better: Harnessing Attention for Interactive Motion Generation and Training-free Editing
Previous motion diffusion models lack explicit modeling of the word-level text-motion correspondence and good explainability, hence restricting their fine-grained editing ability.
MotionCraft: Crafting Whole-Body Motion with Plug-and-Play Multimodal Controls
However, employing a unified model to achieve various generation tasks with different condition modalities presents two main challenges: motion distribution drifts across different tasks (e. g., co-speech gestures and text-driven daily actions) and the complex optimization of mixed conditions with varying granularities (e. g., text and audio).
Image Inpainting Models are Effective Tools for Instruction-guided Image Editing
The most advanced methods, such as SmartEdit and MGIE, usually combine large language models with diffusion models through joint training, where the former provides text understanding ability, and the latter provides image generation ability.
MiraData: A Large-Scale Video Dataset with Long Durations and Structured Captions
Sora's high-motion intensity and long consistent videos have significantly impacted the field of video generation, attracting unprecedented attention.
BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion
Image inpainting, the process of restoring corrupted images, has seen significant advancements with the advent of diffusion models (DMs).
FastVideoEdit: Leveraging Consistency Models for Efficient Text-to-Video Editing
By leveraging the self-consistency property of CMs, we eliminate the need for time-consuming inversion or additional condition extraction, reducing editing time.
VLPose: Bridging the Domain Gap in Pose Estimation with Language-Vision Tuning
Our research aims to bridge the domain gap between natural and artificial scenarios with efficient tuning strategies.
Multi-Patch Prediction: Adapting LLMs for Time Series Representation Learning
In this study, we present aLLM4TS, an innovative framework that adapts Large Language Models (LLMs) for time-series representation learning.
Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
Specifically, in the context of diffusion-based editing, where a source image is edited according to a target prompt, the process commences by acquiring a noisy latent vector corresponding to the source image via the diffusion model.
Ranked #5 on
Text-based Image Editing
on PIE-Bench
HumanSD: A Native Skeleton-Guided Diffusion Model for Human Image Generation
While such a plug-and-play approach is appealing, the inevitable and uncertain conflicts between the original images produced from the frozen SD branch and the given condition incur significant challenges for the learnable branch, which essentially conducts image feature editing for condition enforcement.
Human-Art: A Versatile Human-Centric Dataset Bridging Natural and Artificial Scenes
Humans have long been recorded in a variety of forms since antiquity.
DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation
This paper proposes a simple baseline framework for video-based 2D/3D human pose estimation that can achieve 10 times efficiency improvement over existing works without any performance degradation, named DeciWatch.
Ranked #1 on
2D Human Pose Estimation
on JHMDB (2D poses only)
SmoothNet: A Plug-and-Play Network for Refining Human Poses in Videos
With a simple yet effective motion-aware fully-connected network, SmoothNet improves the temporal smoothness of existing pose estimators significantly and enhances the estimation accuracy of those challenging frames as a side-effect.
