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Found 13 papers, 8 papers with code
AIPO: Improving Training Objective for Iterative Preference Optimization
Despite its success, our study shows that the length exploitation issue present in PO is even more severe in Iterative Preference Optimization (IPO) due to the iterative nature of the process.
Beyond Raw Videos: Understanding Edited Videos with Large Multimodal Model
However, a large portion of videos in real-world applications are edited videos, \textit{e. g.}, users usually cut and add effects/modifications to the raw video before publishing it on social media platforms.
CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts
Recent advancements in Multimodal Large Language Models (LLMs) have focused primarily on scaling by increasing text-image pair data and enhancing LLMs to improve performance on multimodal tasks.
Ranked #1 on
visual instruction following
on LLaVA-Bench
QuadraNet V2: Efficient and Sustainable Training of High-Order Neural Networks with Quadratic Adaptation
Machine learning is evolving towards high-order models that necessitate pre-training on extensive datasets, a process associated with significant overheads.
Steam Recommendation System
The final output of the project is a recommendation system that gives a list of the top 5 items that the users will possibly like. 6
SC-Transformer++: Structured Context Transformer for Generic Event Boundary Detection
This report presents the algorithm used in the submission of Generic Event Boundary Detection (GEBD) Challenge at CVPR 2022.
Structured Context Transformer for Generic Event Boundary Detection
To capture temporal context information of each frame, we design the structure context transformer (SC-Transformer) by re-partitioning input frame sequence.
End-to-End Compressed Video Representation Learning for Generic Event Boundary Detection
Generic event boundary detection aims to localize the generic, taxonomy-free event boundaries that segment videos into chunks.
Generic Event Boundary Detection Challenge at CVPR 2021 Technical Report: Cascaded Temporal Attention Network (CASTANET)
In this work, we design a Cascaded Temporal Attention Network (CASTANET) for GEBD, which is formed by three parts, the backbone network, the temporal attention module, and the classification module.
Ranked #1 on
Boundary Detection
on Kinetics-400
Stable and Effective One-Step Method for Person Search
In order to process divergence between detection and re-identification, we introduce switchable normalization and gradient centralization to improve the stability of the model.
VisDrone-DET2019: The Vision Meets Drone Object Detection in Image Challenge Results
Results of 33 object detection algorithms are presented.
Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
Then we propose a novel loss function, named Adaptive Wing loss, that is able to adapt its shape to different types of ground truth heatmap pixels.
Ranked #8 on
Face Alignment
on WFW (Extra Data)
The morphodynamics of 3D migrating cancer cells
As a result, cell morphodynamics is mapped into temporal evolution of morphological phenotypes.
