Search Results for author:
Found 5 papers, 3 papers with code
LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models
To this end, we proposed the layer pruning and normalized distillation for compressing diffusion models (LAPTOP-Diff).
SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation
In contrast to vanilla consistency distillation (CD) which distills the ordinary differential equation solvers-based sampling process of a pretrained teacher model into a student, SCott explores the possibility and validates the efficacy of integrating stochastic differential equation (SDE) solvers into CD to fully unleash the potential of the teacher.
PEA-Diffusion: Parameter-Efficient Adapter with Knowledge Distillation in non-English Text-to-Image Generation
In this paper, we are inspired to propose a simple plug-and-play language transfer method based on knowledge distillation.
Cross-lingual Text-to-Image Generation
Knowledge Distillation
+1
Instruct-ReID: A Multi-purpose Person Re-identification Task with Instructions
This paper strives to resolve this problem by proposing a new instruct-ReID task that requires the model to retrieve images according to the given image or language instructions.
HumanBench: Towards General Human-centric Perception with Projector Assisted Pretraining
Specifically, we propose a \textbf{HumanBench} based on existing datasets to comprehensively evaluate on the common ground the generalization abilities of different pretraining methods on 19 datasets from 6 diverse downstream tasks, including person ReID, pose estimation, human parsing, pedestrian attribute recognition, pedestrian detection, and crowd counting.
Ranked #1 on
Pedestrian Attribute Recognition
on PA-100K
(using extra training data)
