Search Results for author: Haiwen Feng

Found 16 papers, 5 papers with code

ETCH: Generalizing Body Fitting to Clothed Humans via Equivariant Tightness

1 code implementation13 Mar 2025 Boqian Li, Haiwen Feng, Zeyu Cai, Michael J. Black, Yuliang Xiu

We propose Equivariant Tightness Fitting for Clothed Humans, or ETCH, a novel pipeline that estimates cloth-to-body surface mapping through locally approximate SE(3) equivariance, encoding tightness as displacement vectors from the cloth surface to the underlying body.

3D Human Pose Estimation 3D Human Shape Estimation +2

Predicting 4D Hand Trajectory from Monocular Videos

no code implementations14 Jan 2025 Yufei Ye, Yao Feng, Omid Taheri, Haiwen Feng, Shubham Tulsiani, Michael J. Black

We present HaPTIC, an approach that infers coherent 4D hand trajectories from monocular videos.

Pose Estimation

InterDyn: Controllable Interactive Dynamics with Video Diffusion Models

no code implementations CVPR 2025 Rick Akkerman, Haiwen Feng, Michael J. Black, Dimitrios Tzionas, Victoria Fernández Abrevaya

To address this gap, we propose InterDyn, a novel framework that generates videos of interactive dynamics given an initial frame and a control signal encoding the motion of a driving object or actor.

Video Generation

GenLit: Reformulating Single-Image Relighting as Video Generation

no code implementations15 Dec 2024 Shrisha Bharadwaj, Haiwen Feng, Giorgio Becherini, Victoria Abrevaya, Michael J. Black

Manipulating the illumination of a 3D scene within a single image represents a fundamental challenge in computer vision and graphics.

Image Generation Image Relighting +2

Toward Human Understanding with Controllable Synthesis

no code implementations13 Nov 2024 Hanz Cuevas-Velasquez, Priyanka Patel, Haiwen Feng, Michael Black

While BEDLAM demonstrates the potential of traditional procedural graphics to generate such data, the training images are clearly synthetic.

Can Large Language Models Understand Symbolic Graphics Programs?

no code implementations15 Aug 2024 Zeju Qiu, Weiyang Liu, Haiwen Feng, Zhen Liu, Tim Z. Xiao, Katherine M. Collins, Joshua B. Tenenbaum, Adrian Weller, Michael J. Black, Bernhard Schölkopf

While LLMs exhibit impressive skills in general program synthesis and analysis, symbolic graphics programs offer a new layer of evaluation: they allow us to test an LLM's ability to answer different-grained semantic-level questions of the images or 3D geometries without a vision encoder.

Instruction Following Program Synthesis

SynthForge: Synthesizing High-Quality Face Dataset with Controllable 3D Generative Models

no code implementations12 Jun 2024 Abhay Rawat, Shubham Dokania, Astitva Srivastava, Shuaib Ahmed, Haiwen Feng, Rahul Tallamraju

However, using the data generated using such models for training downstream tasks remains under-explored, mainly due to the lack of 3D consistent annotations.

Re-Thinking Inverse Graphics With Large Language Models

no code implementations23 Apr 2024 Peter Kulits, Haiwen Feng, Weiyang Liu, Victoria Abrevaya, Michael J. Black

Inverse graphics -- the task of inverting an image into physical variables that, when rendered, enable reproduction of the observed scene -- is a fundamental challenge in computer vision and graphics.

Language Modelling Large Language Model +2

Explorative Inbetweening of Time and Space

no code implementations21 Mar 2024 Haiwen Feng, Zheng Ding, Zhihao Xia, Simon Niklaus, Victoria Abrevaya, Michael J. Black, Xuaner Zhang

We introduce bounded generation as a generalized task to control video generation to synthesize arbitrary camera and subject motion based only on a given start and end frame.

Denoising Video Generation

Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization

1 code implementation10 Nov 2023 Weiyang Liu, Zeju Qiu, Yao Feng, Yuliang Xiu, Yuxuan Xue, Longhui Yu, Haiwen Feng, Zhen Liu, Juyeon Heo, Songyou Peng, Yandong Wen, Michael J. Black, Adrian Weller, Bernhard Schölkopf

We apply this parameterization to OFT, creating a novel parameter-efficient finetuning method, called Orthogonal Butterfly (BOFT).

Controlling Text-to-Image Diffusion by Orthogonal Finetuning

2 code implementations NeurIPS 2023 Zeju Qiu, Weiyang Liu, Haiwen Feng, Yuxuan Xue, Yao Feng, Zhen Liu, Dan Zhang, Adrian Weller, Bernhard Schölkopf

To tackle this challenge, we introduce a principled finetuning method -- Orthogonal Finetuning (OFT), for adapting text-to-image diffusion models to downstream tasks.

Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation

no code implementations8 May 2022 Haiwen Feng, Timo Bolkart, Joachim Tesch, Michael J. Black, Victoria Abrevaya

Our experimental results show significant improvement compared to state-of-the-art methods on albedo estimation, both in terms of accuracy and fairness.

Fairness

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