Original Tweet
IGGT: Instance-Grounded Geometry Transformer for Semantic 3D Reconstruction https://lifuguan.github.io/IGGT_official/ Humans naturally perceive both geometric structure and semantic content of 3D worlds, but achieving โthe best of both worldsโ has been a grand challenge for AI. Traditional methods decouple 3D reconstruction (low-level geometry) from spatial understanding (high-level semantics), leading to error accumulation and poor generalization. Meanwhile, newer methods attempt to โlockโ 3D models with specific Vision-Language Models (VLMs), which not only limits the modelโs perception capabilities (e.g., inability to distinguish between different instances of the same class) but also hinders extensibility to stronger downstream tasks.
Now, iGGT presents a revolutionary solution. NTU in collaboration with StepFun proposes iGGT (Instance-Grounded Geometry Transformer), an innovative end-to-end large unified Transformer that, for the first time, integrates spatial reconstruction with instance-level contextual understanding.
๐ ์๋ณธ ๋งํฌ
๋ฏธ๋์ด
๐ Related
- 1n-rotary-position-embeddings-rope-are-ubiquitous-across-tra โ ์ฃผ์ : Reconstruction, Transformer
- 1n-rotary-position-embeddings-rope-are-ubiquitous-across-transformers-that โ ์ฃผ์ : Reconstruction, Transformer
- introducing-shaper-a-method-for-robust-conditional-3d-shape-generation-from-casu โ ์ฃผ์ : Reconstruction, Transformer
- vggt-slam-20-real-time-dense-feed-forward-scene-reconstructi โ ์ฃผ์ : Reconstruction, Transformer
- introducing-360anything-our-method-for-lifting-any-perspecti โ ์ฃผ์ : Reconstruction, Transformer