38 citations · 92 across the 25 of their papers we have counts for
27 papers
VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding
Xinhao Li, Yuhan Zhu, Xiangyu Zeng +24
Recent advances in video understanding have spanned motion, long video, and streaming interaction, driving this field toward real-world applications. Despite this progress, current…
4DHumanDiff: Direct Text-to-4DGS Generation for Consistent 360-Degree Dynamic Humans
Renlong Wu, Haoran Chen, Yuxiang Wei +3
Generating high-quality 360-degree dynamic human assets from text prompts is challenging. Existing methods usually synthesize monocular or multi-view videos first and then fit a 4D…
To Blend In, First Decouple: Rethinking Camouflage Image Generation via Context-Decoupled Representations
Wenzhuang Wang, Yifan Zhao, Mingcan Ma +4
Camouflage image generation (CIG) focuses on generating visually concealed objects that seamlessly blend into their backgrounds. Existing methods typically follow either background…
TimeLens2: Generalist Video Temporal Grounding with Multimodal LLMs
Yuhan Zhu, Changlian Ma, Xiangyu Zeng +12
Video multimodal large language models (MLLMs) can describe what happens in a video, but rarely identify when the supporting evidence occurs. We study generalist video temporal gro…
Flow-based Policy Adaptation without Policy Updates
Luzhe Sun, Jingtian Ji, Haoran Chen +2
Foundation models and other policies trained on large and diverse datasets can endow robots with semantic and task knowledge that would be difficult to acquire from task-specific d…
CameraNoise: Enabling Faithful Camera Control in Video Diffusion through Geometry-Flow-Guided Noise Warping
Haoyu Zhao, Jiaxi Gu, Haoran Chen +11
Precise camera pose control is critical for video diffusion, yet maintaining geometric consistency remains a challenge. Existing methods that directly inject numerical camera param…
Enhancing SignSGD: Small-Batch Convergence Analysis and a Hybrid Switching Strategy
Haoran Chen, Wentao Wang
SignSGD compresses each stochastic gradient coordinate to a single bit, offering substantial memory and communication savings, but its 1-bit quantization removes magnitude informat…
CT-1: Vision-Language-Camera Models Transfer Spatial Reasoning Knowledge to Camera-Controllable Video Generation
Haoyu Zhao, Zihao Zhang, Jiaxi Gu +10
Camera-controllable video generation aims to synthesize videos with flexible and physically plausible camera movements. However, existing methods either provide imprecise camera co…
Think, Then Verify: A Hypothesis-Verification Multi-Agent Framework for Long Video Understanding
Zheng Wang, Haoran Chen, Haoxuan Qin +3
Long video understanding is challenging due to dense visual redundancy, long-range temporal dependencies, and the tendency of chain-of-thought and retrieval-based agents to accumul…
Preserving Cross-Modal Consistency for CLIP-based Class-Incremental Learning
Haoran Chen, Houze Xu, Micah Goldblum +2
Class-incremental learning (CIL) enables models to continuously learn new categories from sequential tasks without forgetting previously acquired knowledge. While recent advances i…
Multi-Prompt Progressive Alignment for Multi-Source Unsupervised Domain Adaptation
Haoran Chen, Zexiao Wang, Haidong Cao +2
Large Vision-Language Models like CLIP have become a powerful foundation for Unsupervised Domain Adaptation due to their strong zero-shot generalization. State-of-the-art methods t…
Multimodal Language Models See Better When They Look Shallower
Haoran Chen, Junyan Lin, Xinghao Chen +6
Multimodal large language models (MLLMs) typically extract visual features from the final layers of a pretrained Vision Transformer (ViT). This widespread deep-layer bias, however,…
Multi-Layer Visual Feature Fusion in Multimodal LLMs: Methods, Analysis, and Best Practices
Junyan Lin, Haoran Chen, Yue Fan +5
Multimodal Large Language Models (MLLMs) have made significant advancements in recent years, with visual features playing an increasingly critical role in enhancing model performan…
EDEN: Enhanced Diffusion for High-quality Large-motion Video Frame Interpolation
Zihao Zhang, Haoran Chen, Haoyu Zhao +4
Handling complex or nonlinear motion patterns has long posed challenges for video frame interpolation. Although recent advances in diffusion-based methods offer improvements over t…
Achieving More with Less: Additive Prompt Tuning for Rehearsal-Free Class-Incremental Learning
Haoran Chen, Ping Wang, Zihan Zhou +3
Class-incremental learning (CIL) enables models to learn new classes progressively while preserving knowledge of previously learned ones. Recent advances in this field have shifted…
A Benchmark for Crime Surveillance Video Analysis with Large Models
Haoran Chen, Dong Yi, Moyan Cao +3
Anomaly analysis in surveillance videos is a crucial topic in computer vision. In recent years, multimodal large language models (MLLMs) have outperformed task-specific models in v…
ForgerySleuth: Empowering Multimodal Large Language Models for Image Manipulation Detection
Zhihao Sun, Haoran Jiang, Haoran Chen +4
Multimodal large language models have unlocked new possibilities for various multimodal tasks. However, their potential in image manipulation detection remains unexplored. When dir…
To Preserve or To Compress: An In-Depth Study of Connector Selection in Multimodal Large Language Models
Junyan Lin, Haoran Chen, Dawei Zhu +1
In recent years, multimodal large language models (MLLMs) have garnered significant attention from both industry and academia. However, there is still considerable debate on constr…
Recurrent Context Compression: Efficiently Expanding the Context Window of LLM
Chensen Huang, Guibo Zhu, Xuepeng Wang +5
To extend the context length of Transformer-based large language models (LLMs) and improve comprehension capabilities, we often face limitations due to computational resources and…
Adaptive Retention & Correction: Test-Time Training for Continual Learning
Haoran Chen, Micah Goldblum, Zuxuan Wu +1
Continual learning, also known as lifelong learning or incremental learning, refers to the process by which a model learns from a stream of incoming data over time. A common proble…
A Survey on Video Diffusion Models
Zhen Xing, Qijun Feng, Haoran Chen +5
The recent wave of AI-generated content (AIGC) has witnessed substantial success in computer vision, with the diffusion model playing a crucial role in this achievement. Due to the…
Panoptic Vision-Language Feature Fields
Haoran Chen, Kenneth Blomqvist, Francesco Milano +1
Recently, methods have been proposed for 3D open-vocabulary semantic segmentation. Such methods are able to segment scenes into arbitrary classes based on text descriptions provide…
PromptFusion: Decoupling Stability and Plasticity for Continual Learning
Haoran Chen, Zuxuan Wu, Xintong Han +2
Current research on continual learning mainly focuses on relieving catastrophic forgetting, and most of their success is at the cost of limiting the performance of newly incoming t…
Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation
Haoran Chen, Xintong Han, Zuxuan Wu +1
Most existing methods for unsupervised domain adaptation (UDA) rely on a shared network to extract domain-invariant features. However, when facing multiple source domains, optimizi…