Unverified50% confidenceFactExact time
If the body parts in LoRA training images contain compression artifacts, low-quality materials, or inconsistent resolutions, the model may learn noise features into skin textures.
1
Sources
50%
Confidence
Long-term
Relevance
9/12/2026
First Seen
Sources
Related Entities
Related Claims
Unverified低质量或过度压缩的训练图像会导致模型在细节生成上产生伪影、色彩失真乃至风格理解偏差75% similarUnverifiedThe Hunyuan model tends to over-simplify and over-smooth, losing realism such as skin texture in photorealistic character tests.74% similarVerifiedIn 2019, researchers at the University of Tübingen discovered that CNN models pre-trained on ImageNet rely more on texture features than shape features when recognizing objects, a phenomenon known as texture bias.71% similarUnverifiedAdversarial sample attacks can add noise to images that is nearly imperceptible to the human eye yet causes models to produce incorrect classifications70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/916460API
curl https://kongchang.com/api/v1/knowledge/claims/916460MCP
get_claim(id=916460)