Search Results for author:
Found 7 papers, 7 papers with code
Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models
Conversation agents fueled by Large Language Models (LLMs) are providing a new way to interact with visual data.
Ranked #1 on
Video-based Generative Performance Benchmarking (Temporal Understanding)
on VideoInstruct
Video-based Generative Performance Benchmarking (Consistency)
Video-based Generative Performance Benchmarking (Contextual Understanding)
+5
SwiftFormer: Efficient Additive Attention for Transformer-based Real-time Mobile Vision Applications
Using our proposed efficient additive attention, we build a series of models called "SwiftFormer" which achieves state-of-the-art performance in terms of both accuracy and mobile inference speed.
UNETR++: Delving into Efficient and Accurate 3D Medical Image Segmentation
Owing to the success of transformer models, recent works study their applicability in 3D medical segmentation tasks.
Fine-tuned CLIP Models are Efficient Video Learners
Since training on a similar scale for videos is infeasible, recent approaches focus on the effective transfer of image-based CLIP to the video domain.
MaPLe: Multi-modal Prompt Learning
Pre-trained vision-language (V-L) models such as CLIP have shown excellent generalization ability to downstream tasks.
Ranked #1 on
Prompt Engineering
on FGVC-Aircraft
Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection
Two popular forms of weak-supervision used in open-vocabulary detection (OVD) include pretrained CLIP model and image-level supervision.
Ranked #1 on
Open Vocabulary Object Detection
on OpenImages-v4
Open Vocabulary Attribute Detection
Zero-Shot Object Detection
Class-agnostic Object Detection with Multi-modal Transformer
This has been a long-standing question in computer vision.
Ranked #1 on
Class-agnostic Object Detection
on COCO
