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ATI

bytedance-research

> **ATI: Any Trajectory Instruction for Controllable Video Generation** > Angtian Wang, Haibin Huang, Jacob Zhiyuan Fang, Yiding Yang, Chongyang Ma, > Intelligent Creation Team, ByteDance This is the repo for Wan2.1 ATI (Any Trajectory Instruction for Controllable Video Generation), a trajectory-based motion control framework that unifies object, local and camera movements in video generation. This repo is based on Wan2.1 offical implementation. Code: https://github.com/bytedance/ATI Finally, copy VAE, T5 and other misc checkpoint from origin Wan2.1 folder to ATI checkpoint location

Input Image→ Output Video
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ChatTS-14B

bytedance-research

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

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Input Text→ Output Text
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ChatTS-8B

bytedance-research

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

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Input Text→ Output Text
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Lance

bytedance-research

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

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Category pending
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LVFace

bytedance-research

--> This is the official PyTorch implementation for the inference of LVFace. Drawing inspiration from the massive data support, multi-stage training paradigm, and Transformer architecture of large-model technology, this method, based on Large Vision Transformer, has carried out progressive optimization of the face clustering space through multiple stages on massive datasets. --> - 🔥🔥🔥 We have released the training weights of LVFace. Please click here to download it. (August, 2025 UTC) - 🎉🎉🎉 LVFace has been recommended as **ICCV Highlight**. (July, 2025 UTC) - 🎉🎉🎉 LVFace is accepted by **ICCV 2025**. (July, 2025 UTC) - 🔥🔥🔥 We have updated the arXiv report of LVFace. Please click here to view it. (March, 2025 UTC) - 🎉🎉🎉 LVFace secured **1st place** in the ICCV 2021 Masked Face Recognition (MFR)-Ongoing Challenge (academic track). (December, 2024 UTC) Test datasets for inference validation can be downloaded from the following sources: - **IJB-C & IJB-B**: Google Drive - **MFR-Ongoing**: Challenge Page

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Timer-S1

bytedance-research

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

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UMO

bytedance-research

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

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Input Text→ Output Image
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