Riza Velioglu
AI & ML interests
Multimodal Models, Diffusion Models, Object Detection & Segmentation
Recent Activity
new activity
about 5 hours ago
fal/virtual-tryoff-lora:Comfy Converted Version? updated
a model about 5 hours ago
fal/virtual-tryoff-lora liked
a model 1 day ago
fal/virtual-tryoff-lora Organizations
Comfy Converted Version?
2
#1 opened about 21 hours ago
by
Runebinder
Team please make a repose lora! PLEASE!
2
#1 opened 8 days ago
by
krigeta
upvoted an article 3 months ago
Article
Continuous batching from first principles
- +1
โข
341
upvoted a paper 7 months ago
replied to their post 8 months ago
A follow-up work named Multi-Garment TryOffDiff (MGT) is now available, which extends capabilities of TryOffDiff to support multi-garment reconstruction, including upper-body, lower-body, and full-body (dress) garments, enabling more comprehensive scenarios.
๐ All scripts for training, inference, and evaluation are included.
Check it out on GitHub: https://github.com/rizavelioglu/tryoffdiff/
replied to their post 8 months ago
๐ฅณ The code has now been published!
Find the training, inference, and evaluation scripts in the repo: https://github.com/rizavelioglu/tryoffdiff/
posted an
update 9 months ago
Post
949
TryOffDiff goes multi-garment!
We're excited to share TryOffDiff v2, extending our approach to support multiple garment categories. Key updates include:
- Training on the multi-garment DressCode dataset, covering upper-body, lower-body, and dresses.
- A simplified adapter design for improved training efficiency and modularity.
- Introduction of four specialized models:
- One model per category (upper, lower, dress),
- Plus a multi-garment model capable of generating multiple garments sequentially from a single image.
*PS:* Visit us this Friday at 10:30 AM in ExHall-B for our live demo @CVPR '25!
Demo: rizavelioglu/tryoffdiff
Project page: https://rizavelioglu.github.io/tryoffdiff
We're excited to share TryOffDiff v2, extending our approach to support multiple garment categories. Key updates include:
- Training on the multi-garment DressCode dataset, covering upper-body, lower-body, and dresses.
- A simplified adapter design for improved training efficiency and modularity.
- Introduction of four specialized models:
- One model per category (upper, lower, dress),
- Plus a multi-garment model capable of generating multiple garments sequentially from a single image.
*PS:* Visit us this Friday at 10:30 AM in ExHall-B for our live demo @CVPR '25!
Demo: rizavelioglu/tryoffdiff
Project page: https://rizavelioglu.github.io/tryoffdiff