1.8k citations · 3.8k across the 131 of their papers we have counts for
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Preference Alignment for Diffusion Model via Explicit Denoised Distribution Estimation
Dingyuan Shi, Yong Wang, Hangyu Li +1
Diffusion models have shown remarkable success in text-to-image generation, making preference alignment for these models increasingly important. The preference labels are typically…
FlowDreamer: Exploring High Fidelity Text-to-3D Generation via Rectified Flow
Hangyu Li, Xiangxiang Chu, Dingyuan Shi +1
Recent advances in text-to-3D generation have made significant progress. In particular, with the pretrained diffusion models, existing methods predominantly use Score Distillation…
Dyn-Adapter: Towards Disentangled Representation for Efficient Visual Recognition
Yurong Zhang, Honghao Chen, Xinyu Zhang +2
Parameter-efficient transfer learning (PETL) is a promising task, aiming to adapt the large-scale pre-trained model to downstream tasks with a relatively modest cost. However, curr…
Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
Honghao Chen, Yurong Zhang, Xiaokun Feng +2
Robustness is a vital aspect to consider when deploying deep learning models into the wild. Numerous studies have been dedicated to the study of the robustness of vision transforme…
PLUG: Revisiting Amodal Segmentation with Foundation Model and Hierarchical Focus
Zhaochen Liu, Limeng Qiao, Xiangxiang Chu +1
Aiming to predict the complete shapes of partially occluded objects, amodal segmentation is an important step towards visual intelligence. With crucial significance, practical prio…
AdaFedFR: Federated Face Recognition with Adaptive Inter-Class Representation Learning
Di Qiu, Xinyang Lin, Kaiye Wang +2
With the growing attention on data privacy and communication security in face recognition applications, federated learning has been introduced to learn a face recognition model wit…
DSFNet: Learning Disentangled Scenario Factorization for Multi-Scenario Route Ranking
Jiahao Yu, Yihai Duan, Longfei Xu +6
Multi-scenario route ranking (MSRR) is crucial in many industrial mapping systems. However, the industrial community mainly adopts interactive interfaces to encourage users to sele…
PeLK: Parameter-efficient Large Kernel ConvNets with Peripheral Convolution
Honghao Chen, Xiangxiang Chu, Yongjian Ren +2
Recently, some large kernel convnets strike back with appealing performance and efficiency. However, given the square complexity of convolution, scaling up kernels can bring about…
Adaptive Task Balancing for Visual Instruction Tuning via Inter-Task Contribution and Intra-Task Difficulty
Yanqi Dai, Yong Wang, Zebin You +3
Visual instruction tuning is a key training stage of large multimodal models. However, when learning multiple visual tasks simultaneously, this approach often results in suboptimal…
VisionLLaMA: A Unified LLaMA Backbone for Vision Tasks
Xiangxiang Chu, Jianlin Su, Bo Zhang +1
Large language models are built on top of a transformer-based architecture to process textual inputs. For example, the LLaMA stands out among many open-source implementations. Can…
MobileVLM V2: Faster and Stronger Baseline for Vision Language Model
Xiangxiang Chu, Limeng Qiao, Xinyu Zhang +8
We introduce MobileVLM V2, a family of significantly improved vision language models upon MobileVLM, which proves that a delicate orchestration of novel architectural design, an im…
LiDAR-PTQ: Post-Training Quantization for Point Cloud 3D Object Detection
Sifan Zhou, Liang Li, Xinyu Zhang +6
Due to highly constrained computing power and memory, deploying 3D lidar-based detectors on edge devices equipped in autonomous vehicles and robots poses a crucial challenge. Being…
SCTNet: Single-Branch CNN with Transformer Semantic Information for Real-Time Segmentation
Zhengze Xu, Dongyue Wu, Changqian Yu +3
Recent real-time semantic segmentation methods usually adopt an additional semantic branch to pursue rich long-range context. However, the additional branch incurs undesirable comp…