Unverified50% confidenceFactExact time
SUPRA-TEX is a framework for generating material-bearing, relightable 3D assets from a single image; by decoupling visible material estimation, surface alignment, and observation-guided 3D completion, it reaches SOTA level when trained only on public datasets.
1
Sources
50%
Confidence
Long-term
Relevance
10/16/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedIn stage two, SUPRA-TEX projects the predicted PBR maps onto the visible surface and converts them, through a pretrained material VAE encoder, into 'native observation latents' that share the same latent space as the generation target, in order to achieve hyper-alignment.62% similarUnverifiedDify provides a visual workflow orchestration interface with built-in capabilities including vector storage, document chunking, and RAG retrieval.60% similarUnverifiedColPali is a representative visual retrieval solution that renders document pages as images and uses a vision-language model to extract patch-level multi-vector representations, bypassing the OCR step.60% similarUnverifiedTiled processing is a classic VRAM optimization technique in the image generation field, first widely used in high-resolution upscaling scenarios with Stable Diffusion.57% similarUnverifiedGradCAM (Gradient-weighted Class Activation Mapping) is a visualization technique that generates heat maps showing the regions of a medical image that an AI focuses on.57% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1042487API
curl https://kongchang.com/api/v1/knowledge/claims/1042487MCP
get_claim(id=1042487)