This system includes two foundation components: a large-scale shape generation model -- Hunyuan3D-DiT, and a large-scale texture synthesis model -- Hunyuan3D-Paint.
This paper introduces UI-TARS, a native GUI agent model that solely perceives the screenshots as input and performs human-like interactions (e. g., keyboard and mouse operations).
The efficiency of our algorithm enables us to fine-tune modern video diffusion base models using warped noise with minimal overhead, and provide a one-stop solution for a wide range of user-friendly motion control: local object motion control, global camera movement control, and motion transfer.
The key insight of our vision-centric training paradigm is that high-quality image-text data is crucial for both image and video understanding.
We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token.
The rapid development of open-source large language models (LLMs) has been truly remarkable.
IntellAgent represents a paradigm shift in evaluating conversational AI.
Notably, PaSa-7B surpasses the best Google-based baseline, Google with GPT-4o, by 37. 78% in recall@20 and 39. 90% in recall@50.
We hope our study provides unique insights and paves a new path for integrating CoT reasoning with autoregressive image generation.
Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using information from neighboring frames, while completing masked regions through visual Transformers.