REVIEW 12 cited by
AnchorCrafter: Animate Cyber-Anchors Selling Your Products via Human-Object Interacting Video Generation
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
The generation of anchor-style product promotion videos presents promising opportunities in e-commerce, advertising, and consumer engagement. Despite advancements in pose-guided human video generation, creating product promotion videos remains challenging. In addressing this challenge, we identify the integration of human-object interactions (HOI) into pose-guided human video generation as a core issue. To this end, we introduce AnchorCrafter, a novel diffusion-based system designed to generate 2D videos featuring a target human and a customized object, achieving high visual fidelity and controllable interactions. Specifically, we propose two key innovations: the HOI-appearance perception, which enhances object appearance recognition from arbitrary multi-view perspectives and disentangles object and human appearance, and the HOI-motion injection, which enables complex human-object interactions by overcoming challenges in object trajectory conditioning and inter-occlusion management. Extensive experiments show that our system improves object appearance preservation by 7.5\% and doubles the object localization accuracy compared to existing state-of-the-art approaches. It also outperforms existing approaches in maintaining human motion consistency and high-quality video generation. Project page including data, code, and Huggingface demo: https://github.com/cangcz/AnchorCrafter.
Forward citations
Cited by 12 Pith papers
-
HarmoHOI: Harmonizing Appearance and 3D Motion for Multi-view Hand-Object Interaction Synthesis
HarmoHOI jointly generates synchronized multi-view hand-object interaction videos and globally aligned 3D point tracks from a single reference image and target camera poses.
-
AgentHOI: Multi-Agent Reasoning for Human-Object-Interaction Video Generation via Implicit Representation Alignment
AgentHOI generates human-object interaction videos from text plus one human image and one object image, using multi-agent action planning and implicit text-to-motion feature alignment inside a video diffusion model.
-
StreamHOI: Interaction-aware Temporal Memory Adaptation for Streaming HOI Video Generation
A streaming image-to-video model that assigns block-specific sink/local memory and learned RoPE distance scaling preserves long human-object interactions under bounded latency.
-
HOMIE: Human-object Centric Video Personalization via Multimodal Intelligent Enhancement
HOMIE unifies inter- and intra-subject video personalization by injecting MLLM-derived relational features into DiT self-attention (GMG) and tagging tokens with modality/reference embeddings (MRE), reporting SOTA on a...
-
AHOY! Animatable Humans under Occlusion from YouTube Videos with Gaussian Splatting and Video Diffusion Priors
Identity-finetuned video diffusion plus RF-Inversion can supply multi-view body supervision that lets 3D Gaussian avatars be completed and animated from heavily occluded monocular video.
-
MVHOI: Bridge Multi-view Condition to Complex Human-Object Interaction Video Reenactment via 3D Foundation Model
Using a 3D foundation model to produce viewpoint-aware anchors plus multi-view reference textures enables realistic human-object-interaction reenactment with large out-of-plane rotations.
-
HOComp: Interaction-Aware Human-Object Composition
A diffusion-transformer method that composes a foreground object into a human image with MLLM-chosen interaction regions, pose keypoint supervision, and appearance/background consistency losses, plus a new paired dataset.
-
DreamActor-H1: High-Fidelity Human-Product Demonstration Video Generation via Motion-designed Diffusion Transformers
A diffusion transformer model generates human-product demonstration videos from paired human and product images while preserving both identities through masked cross-attention and motion template guidance.
-
HunyuanVideo-HOMA: Generic Human-Object Interaction in Multimodal Driven Human Animation
HunyuanVideo-HOMA generates human-object interaction videos from weak, sparse inputs: one arm pose, an object center dot, a human photo, and an object photo.
-
SViMo: Synchronized Diffusion for Video and Motion Generation in Hand-object Interaction Scenarios
SViMo jointly generates HOI videos and explicit 3D hand-object motion via synchronized diffusion with a closed-loop 3D interaction diffusion model.
-
Real-Time Human-Centric World Modeling for Upper-Body Human-Object Interaction
A distilled video model jointly controls multi-scale upper-body motion latents and two discrete contact states to generate real-time human–object interaction at 25 FPS.
-
DreamSwapV: Mask-guided Subject Swapping for Any Customized Video Editing
DreamSwapV performs mask-guided, subject-agnostic subject swapping in videos using multiple conditions, an adaptive mask strategy, and a new benchmark.
Discussion (0). Sign in to comment.