Search Results for author:
Found 11 papers, 7 papers with code
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
We try to narrow the gap by mining the potential of VLMs for better performance and any-to-any workflow from three aspects, i. e., high-resolution visual tokens, high-quality data, and VLM-guided generation.
Ranked #8 on
Visual Question Answering
on MM-Vet
RL-GPT: Integrating Reinforcement Learning and Code-as-policy
To seamlessly integrate both modalities, we introduce a two-level hierarchical framework, RL-GPT, comprising a slow agent and a fast agent.
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 #3 on
Text-based Image Editing
on PIE-Bench
Self-supervised Learning by View Synthesis
In each iteration, the input to VSA is one view (or multiple views) of a 3D object and the output is a synthesized image in another target pose.
Video-P2P: Video Editing with Cross-attention Control
This paper presents Video-P2P, a novel framework for real-world video editing with cross-attention control.
Generative Model Watermarking Based on Human Visual System
Intellectual property protection of deep neural networks is receiving attention from more and more researchers, and the latest research applies model watermarking to generative models for image processing.
On-target Adaptation
Domain adaptation seeks to mitigate the shift between training on the \emph{source} domain and testing on the \emph{target} domain.
Multi-modal Cooking Workflow Construction for Food Recipes
Understanding food recipe requires anticipating the implicit causal effects of cooking actions, such that the recipe can be converted into a graph describing the temporal workflow of the recipe.
GREEN: a Graph REsidual rE-ranking Network for Grading Diabetic Retinopathy
In this paper, we propose a Graph REsidual rE-ranking Network (GREEN) to introduce a class dependency prior into the original image classification network.
Tent: Fully Test-time Adaptation by Entropy Minimization
A model must adapt itself to generalize to new and different data during testing.
Hyperbolic Visual Embedding Learning for Zero-Shot Recognition
This paper proposes a Hyperbolic Visual Embedding Learning Network for zero-shot recognition.
