103 citations · 544 across the 71 of their papers we have counts for
79 papers · 1 filter
Heavy Labels Out! Dataset Distillation with Label Space Lightening
Ruonan Yu, Songhua Liu, Zigeng Chen +2
Dataset distillation or condensation aims to condense a large-scale training dataset into a much smaller synthetic one such that the training performance of distilled and original…
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Lingfeng Ren +7
MM-Vet, with open-ended vision-language questions targeting at evaluating integrated capabilities, has become one of the most popular benchmarks for large multimodal model evaluati…
Domain-Adaptive 2D Human Pose Estimation via Dual Teachers in Extremely Low-Light Conditions
Yihao Ai, Yifei Qi, Bo Wang +3
Existing 2D human pose estimation research predominantly concentrates on well-lit scenarios, with limited exploration of poor lighting conditions, which are a prevalent aspect of d…
Encapsulating Knowledge in One Prompt
Qi Li, Runpeng Yu, Xinchao Wang
This paradigm encapsulates knowledge from various models into a solitary prompt without altering the original models or requiring access to the training data, which enables us to a…
Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach
Taolin Zhang, Jiawang Bai, Zhihe Lu +4
Recent works on parameter-efficient transfer learning (PETL) show the potential to adapt a pre-trained Vision Transformer to downstream recognition tasks with only a few learnable…
Isomorphic Pruning for Vision Models
Gongfan Fang, Xinyin Ma, Michael Bi Mi +1
Structured pruning reduces the computational overhead of deep neural networks by removing redundant sub-structures. However, assessing the relative importance of different sub-stru…