most citedSeed1.5-VL Technical Report

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2026

CineScene: Implicit 3D as Effective Scene Representation for Cinematic Video Generation

Kaiyi Huang, Yukun Huang, Yu Li +8

Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical se…

cs.CV2025

AdaViewPlanner: Adapting Video Diffusion Models for Viewpoint Planning in 4D Scenes

Yu Li, Menghan Xia, Gongye Liu +7

Recent Text-to-Video (T2V) models have demonstrated powerful capability in visual simulation of real-world geometry and physical laws, indicating its potential as implicit world mo…

cs.CV2025

SimpleGVR: A Simple Baseline for Latent-Cascaded Video Super-Resolution

Liangbin Xie, Yu Li, Shian Du +7

Latent diffusion models have emerged as a leading paradigm for efficient video generation. However, as user expectations shift toward higher-resolution outputs, relying solely on l…

cs.CV2025

Domain-RAG: Retrieval-Guided Compositional Image Generation for Cross-Domain Few-Shot Object Detection

Yu Li, Xingyu Qiu, Yuqian Fu +8

Cross-Domain Few-Shot Object Detection (CD-FSOD) aims to detect novel objects with only a handful of labeled samples from previously unseen domains. While data augmentation and gen…

cs.CV20251 cited

Seed1.5-VL Technical Report

Dong Guo, Faming Wu, Feida Zhu +194

We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…