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20192026
most citedSegmentation Transformer: Object-Contextual Representations for Semantic Segmentation

502 citations · 1.4k across the 190 of their papers we have counts for

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Showing 2024Show all

60 papers · 1 filter

cs.CV2024

Revisiting MLLMs: An In-Depth Analysis of Image Classification Abilities

Huan Liu, Lingyu Xiao, Jiangjiang Liu +4

With the rapid advancement of Multimodal Large Language Models (MLLMs), a variety of benchmarks have been introduced to evaluate their capabilities. While most evaluations have foc…

cs.CV2024

Visual Object Tracking across Diverse Data Modalities: A Review

Mengmeng Wang, Teli Ma, Shuo Xin +5

Visual Object Tracking (VOT) is an attractive and significant research area in computer vision, which aims to recognize and track specific targets in video sequences where the targ…

cs.CV2024

ALoRE: Efficient Visual Adaptation via Aggregating Low Rank Experts

Sinan Du, Guosheng Zhang, Keyao Wang +7

Parameter-efficient transfer learning (PETL) has become a promising paradigm for adapting large-scale vision foundation models to downstream tasks. Typical methods primarily levera…

cs.CV2024

Enhancing Descriptive Captions with Visual Attributes for Multimodal Perception

Yanpeng Sun, Jing Hao, Ke Zhu +6

Training Large Multimodality Models (LMMs) relies on descriptive image caption that connects image and language. Existing methods for generating such captions often rely on distill…

cs.CV2024

Low-Biased General Annotated Dataset Generation

Dengyang Jiang, Haoyu Wang, Lei Zhang +5

Pre-training backbone networks on a general annotated dataset (e.g., ImageNet) that comprises numerous manually collected images with category annotations has proven to be indispen…

cs.CV2024

Hallo3: Highly Dynamic and Realistic Portrait Image Animation with Video Diffusion Transformer

Jiahao Cui, Hui Li, Yun Zhan +7

Existing methodologies for animating portrait images face significant challenges, particularly in handling non-frontal perspectives, rendering dynamic objects around the portrait,…

cs.LG2024

Continual SFT Matches Multimodal RLHF with Negative Supervision

Ke Zhu, Yu Wang, Yanpeng Sun +4

Multimodal RLHF usually happens after supervised finetuning (SFT) stage to continually improve vision-language models' (VLMs) comprehension. Conventional wisdom holds its superiori…

cs.CV2024

TopoSD: Topology-Enhanced Lane Segment Perception with SDMap Prior

Sen Yang, Minyue Jiang, Ziwei Fan +6

Recent advances in autonomous driving systems have shifted towards reducing reliance on high-definition maps (HDMaps) due to the huge costs of annotation and maintenance. Instead,…

cs.CV2024

DGTR: Distributed Gaussian Turbo-Reconstruction for Sparse-View Vast Scenes

Hao Li, Yuanyuan Gao, Haosong Peng +7

Novel-view synthesis (NVS) approaches play a critical role in vast scene reconstruction. However, these methods rely heavily on dense image inputs and prolonged training times, mak…

cs.CV2024

MoLE: Enhancing Human-centric Text-to-image Diffusion via Mixture of Low-rank Experts

Jie Zhu, Yixiong Chen, Mingyu Ding +3

Text-to-image diffusion has attracted vast attention due to its impressive image-generation capabilities. However, when it comes to human-centric text-to-image generation, particul…

cs.CV2024

Schedule Your Edit: A Simple yet Effective Diffusion Noise Schedule for Image Editing

Haonan Lin, Mengmeng Wang, Jiahao Wang +7

Text-guided diffusion models have significantly advanced image editing, enabling high-quality and diverse modifications driven by text prompts. However, effective editing requires…

cs.CV2024

Flipped Classroom: Aligning Teacher Attention with Student in Generalized Category Discovery

Haonan Lin, Wenbin An, Jiahao Wang +6

Recent advancements have shown promise in applying traditional Semi-Supervised Learning strategies to the task of Generalized Category Discovery (GCD). Typically, this involves a t…

cs.CV2024

Improving Multi-modal Large Language Model through Boosting Vision Capabilities

Yanpeng Sun, Huaxin Zhang, Qiang Chen +5

We focus on improving the visual understanding capability for boosting the vision-language models. We propose \textbf{Arcana}, a multiModal language model, which introduces two cru…

cs.CV2024

TALK-Act: Enhance Textural-Awareness for 2D Speaking Avatar Reenactment with Diffusion Model

Jiazhi Guan, Quanwei Yang, Kaisiyuan Wang +9

Recently, 2D speaking avatars have increasingly participated in everyday scenarios due to the fast development of facial animation techniques. However, most existing works neglect…

cs.CV2024★ 3 cited

Hallo2: Long-Duration and High-Resolution Audio-Driven Portrait Image Animation

Jiahao Cui, Hui Li, Yao Yao +6

Recent advances in latent diffusion-based generative models for portrait image animation, such as Hallo, have achieved impressive results in short-duration video synthesis. In this…

cs.CV2024

MGMapNet: Multi-Granularity Representation Learning for End-to-End Vectorized HD Map Construction

Jing Yang, Minyue Jiang, Sen Yang +5

The construction of Vectorized High-Definition (HD) map typically requires capturing both category and geometry information of map elements. Current state-of-the-art methods often…

cs.CV2024

MonoFormer: One Transformer for Both Diffusion and Autoregression

Chuyang Zhao, Yuxing Song, Wenhao Wang +5

Most existing multimodality methods use separate backbones for autoregression-based discrete text generation and diffusion-based continuous visual generation, or the same backbone…

cs.RO2024

Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Driving

Lingyu Xiao, Jiang-Jiang Liu, Sen Yang +4

The autoregressive world model exhibits robust generalization capabilities in vectorized scene understanding but encounters difficulties in deriving actions due to insufficient unc…

cs.CV2024

FullAnno: A Data Engine for Enhancing Image Comprehension of MLLMs

Jing Hao, Yuxiang Zhao, Song Chen +6

Multimodal Large Language Models (MLLMs) have shown promise in a broad range of vision-language tasks with their strong reasoning and generalization capabilities. However, they hea…

cs.CV2024

SpotActor: Training-Free Layout-Controlled Consistent Image Generation

Jiahao Wang, Caixia Yan, Weizhan Zhang +6

Text-to-image diffusion models significantly enhance the efficiency of artistic creation with high-fidelity image generation. However, in typical application scenarios like comic b…

cs.CV2024

Make Your ViT-based Multi-view 3D Detectors Faster via Token Compression

Dingyuan Zhang, Dingkang Liang, Zichang Tan +4

Slow inference speed is one of the most crucial concerns for deploying multi-view 3D detectors to tasks with high real-time requirements like autonomous driving. Although many spar…

cs.RO2024

EasyChauffeur: A Baseline Advancing Simplicity and Efficiency on Waymax

Lingyu Xiao, Jiang-Jiang Liu, Xiaoqing Ye +2

Recent advancements in deep-learning-based driving planners have primarily focused on elaborate network engineering, yielding limited improvements. This paper diverges from convent…

cs.CV2024

Disentangled Noisy Correspondence Learning

Zhuohang Dang, Minnan Luo, Jihong Wang +6

Cross-modal retrieval is crucial in understanding latent correspondences across modalities. However, existing methods implicitly assume well-matched training data, which is impract…

cs.CV2024

ReSyncer: Rewiring Style-based Generator for Unified Audio-Visually Synced Facial Performer

Jiazhi Guan, Zhiliang Xu, Hang Zhou +10

Lip-syncing videos with given audio is the foundation for various applications including the creation of virtual presenters or performers. While recent studies explore high-fidelit…