VLPose : Bridging the Domain Gap in Pose Estimation With Language-Vision Tuning
Thanks to advances in deep learning techniques, Human Pose Estimation (HPE) has achieved significant progress in natural scenarios. However, these models perform poorly in artificial scenarios such as painting and sculpture due to the domain gap, constraining the development of virtual reality and a...
Description complète
Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 47(2025), 11 vom: 01. Okt., Seite 10836-10847
|
|---|
| Auteur principal: |
Li, Jingyao
(Auteur) |
|---|
| Autres auteurs: |
Chen, Pengguang,
Ju, Xuan,
Liu, Shu,
Xu, Hong,
Jia, Jiaya |
|---|
| Format: | Article en ligne
|
|---|
| Langue: | English |
|---|
| Publié: |
2025
|
|---|
| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
|
|---|
| Sujets: | Journal Article |
|---|